Search results for: combined hardening model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18623

Search results for: combined hardening model

16223 Implementation of a Non-Poissonian Model in a Low-Seismicity Area

Authors: Ludivine Saint-Mard, Masato Nakajima, Gloria Senfaute

Abstract:

In areas with low to moderate seismicity, the probabilistic seismic hazard analysis frequently uses a Poisson approach, which assumes independence in time and space of events to determine the annual probability of earthquake occurrence. Nevertheless, in countries with high seismic rate, such as Japan, it is frequently use non-poissonian model which assumes that next earthquake occurrence depends on the date of previous one. The objective of this paper is to apply a non-poissonian models in a region of low to moderate seismicity to get a feedback on the following questions: can we overcome the lack of data to determine some key parameters?, and can we deal with uncertainties to apply largely this methodology on an industrial context?. The Brownian-Passage-Time model was applied to a fault located in France and conclude that even if the lack of data can be overcome with some calculations, the amount of uncertainties and number of scenarios leads to a numerous branches in PSHA, making this method difficult to apply on a large scale of low to moderate seismicity areas and in an industrial context.

Keywords: probabilistic seismic hazard, non-poissonian model, earthquake occurrence, low seismicity

Procedia PDF Downloads 51
16222 Model-Based Approach as Support for Product Industrialization: Application to an Optical Sensor

Authors: Frederic Schenker, Jonathan J. Hendriks, Gianluca Nicchiotti

Abstract:

In a product industrialization perspective, the end-product shall always be at the peak of technological advancement and developed in the shortest time possible. Thus, the constant growth of complexity and a shorter time-to-market calls for important changes on both the technical and business level. Undeniably, the common understanding of the system is beclouded by its complexity which leads to the communication gap between the engineers and the sale department. This communication link is therefore important to maintain and increase the information exchange between departments to ensure a punctual and flawless delivery to the end customer. This evolution brings engineers to reason with more hindsight and plan ahead. In this sense, they use new viewpoints to represent the data and to express the model deliverables in an understandable way that the different stakeholder may identify their needs and ideas. This article focuses on the usage of Model-Based System Engineering (MBSE) in a perspective of system industrialization and reconnect the engineering with the sales team. The modeling method used and presented in this paper concentrates on displaying as closely as possible the needs of the customer. Firstly, by providing a technical solution to the sales team to help them elaborate commercial offers without omitting technicalities. Secondly, the model simulates between a vast number of possibilities across a wide range of components. It becomes a dynamic tool for powerful analysis and optimizations. Thus, the model is no longer a technical tool for the engineers, but a way to maintain and solidify the communication between departments using different views of the model. The MBSE contribution to cost optimization during New Product Introduction (NPI) activities is made explicit through the illustration of a case study describing the support provided by system models to architectural choices during the industrialization of a novel optical sensor.

Keywords: analytical model, architecture comparison, MBSE, product industrialization, SysML, system thinking

Procedia PDF Downloads 151
16221 A Domain Specific Modeling Language Semantic Model for Artefact Orientation

Authors: Bunakiye R. Japheth, Ogude U. Cyril

Abstract:

Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: control process, metrics of engineering, structured abstraction, semantic model

Procedia PDF Downloads 136
16220 Multi-Objective Production Planning Problem: A Case Study of Certain and Uncertain Environment

Authors: Ahteshamul Haq, Srikant Gupta, Murshid Kamal, Irfan Ali

Abstract:

This case study designs and builds a multi-objective production planning model for a hardware firm with certain & uncertain data. During the time of interaction with the manager of the firm, they indicate some of the parameters may be vague. This vagueness in the formulated model is handled by the concept of fuzzy set theory. Triangular & Trapezoidal fuzzy numbers are used to represent the uncertainty in the collected data. The fuzzy nature is de-fuzzified into the crisp form using well-known defuzzification method via graded mean integration representation method. The proposed model attempts to maximize the production of the firm, profit related to the manufactured items & minimize the carrying inventory costs in both certain & uncertain environment. The recommended optimal plan is determined via fuzzy programming approach, and the formulated models are solved by using optimizing software LINGO 16.0 for getting the optimal production plan. The proposed model yields an efficient compromise solution with the overall satisfaction of decision maker.

Keywords: production planning problem, multi-objective optimization, fuzzy programming, fuzzy sets

Procedia PDF Downloads 204
16219 A Quasi-Experimental Study of the Impact of 5Es Instructional Model on Students' Mathematics Achievement in Northern Province, Rwanda

Authors: Emmanuel Iyamuremye, Jean François Maniriho, Irenee Ndayambaje

Abstract:

Mathematics is the foundational enabling discipline that underpins science, technology, and engineering disciplines. Science, technology, engineering, and mathematics (STEM) subjects are foreseen as the engine for socio-economic transformation. Rwanda has done reforms in education aiming at empowering and preparing students for the real world job by providing career pathways in science, technology, engineering, and mathematics related fields. While that considered so, the performance in mathematics has remained deplorable in both formative and national examinations. Therefore, this paper aims at exploring the extent to which the engage, explore, explain, elaborate and evaluate (5Es) instructional model contributing towards students’ achievement in mathematics. The present study adopted the pre-test, post-test non-equivalent control group quasi-experimental design. The 5Es instructional model was applied to the experimental group while the control group received instruction with the conventional teaching method for eight weeks. One research-made instrument, mathematics achievement test (MAT), was used for data collection. A pre-test was given to students before the intervention to make sure that both groups have equivalent characteristics. At the end of the experimental period, the two groups have undergone a post-test to ascertain the contribution of the 5Es instructional model. Descriptive statistics and analysis of covariance (ANCOVA) were used for the analysis of the study. For determining the improvement in mathematics, Hakes methods of calculating gain were used to analyze the pre-test and post-test scores. Results showed that students exposed to 5Es instructional model achieved significantly better performance in mathematics than students instructed using the conventional teaching method. It was also found that 5Es instructional model made lessons more interesting, easy and created friendship among students. Thus, 5Es instructional model was recommended to be adopted as a close substitute to the conventional teaching method in teaching mathematics in lower secondary schools in Rwanda.

Keywords: 5Es instructional model, achievement, conventional teaching method, mathematics

Procedia PDF Downloads 99
16218 The Optimal Order Policy for the Newsvendor Model under Worker Learning

Authors: Sunantha Teyarachakul

Abstract:

We consider the worker-learning Newsvendor Model, under the case of lost-sales for unmet demand, with the research objective of proposing the cost-minimization order policy and lot size, scheduled to arrive at the beginning of the selling-period. In general, the New Vendor Model is used to find the optimal order quantity for the perishable items such as fashionable products or those with seasonal demand or short-life cycles. Technically, it is used when the product demand is stochastic and available for the single selling-season, and when there is only a one time opportunity for the vendor to purchase, with possibly of long ordering lead-times. Our work differs from the classical Newsvendor Model in that we incorporate the human factor (specifically worker learning) and its influence over the costs of processing units into the model. We describe this by using the well-known Wright’s Learning Curve. Most of the assumptions of the classical New Vendor Model are still maintained in our work, such as the constant per-unit cost of leftover and shortage, the zero initial inventory, as well as the continuous time. Our problem is challenging in the way that the best order quantity in the classical model, which is balancing the over-stocking and under-stocking costs, is no longer optimal. Specifically, when adding the cost-saving from worker learning to such expected total cost, the convexity of the cost function will likely not be maintained. This has called for a new way in determining the optimal order policy. In response to such challenges, we found a number of characteristics related to the expected cost function and its derivatives, which we then used in formulating the optimal ordering policy. Examples of such characteristics are; the optimal order quantity exists and is unique if the demand follows a Uniform Distribution; if the demand follows the Beta Distribution with some specific properties of its parameters, the second derivative of the expected cost function has at most two roots; and there exists the specific level of lot size that satisfies the first order condition. Our research results could be helpful for analysis of supply chain coordination and of the periodic review system for similar problems.

Keywords: inventory management, Newsvendor model, order policy, worker learning

Procedia PDF Downloads 409
16217 Discrimination and Classification of Vestibular Neuritis Using Combined Fisher and Support Vector Machine Model

Authors: Amine Ben Slama, Aymen Mouelhi, Sondes Manoubi, Chiraz Mbarek, Hedi Trabelsi, Mounir Sayadi, Farhat Fnaiech

Abstract:

Vertigo is a sensation of feeling off balance; the cause of this symptom is very difficult to interpret and needs a complementary exam. Generally, vertigo is caused by an ear problem. Some of the most common causes include: benign paroxysmal positional vertigo (BPPV), Meniere's disease and vestibular neuritis (VN). In clinical practice, different tests of videonystagmographic (VNG) technique are used to detect the presence of vestibular neuritis (VN). The topographical diagnosis of this disease presents a large diversity in its characteristics that confirm a mixture of problems for usual etiological analysis methods. In this study, a vestibular neuritis analysis method is proposed with videonystagmography (VNG) applications using an estimation of pupil movements in the case of an uncontrolled motion to obtain an efficient and reliable diagnosis results. First, an estimation of the pupil displacement vectors using with Hough Transform (HT) is performed to approximate the location of pupil region. Then, temporal and frequency features are computed from the rotation angle variation of the pupil motion. Finally, optimized features are selected using Fisher criterion evaluation for discrimination and classification of the VN disease.Experimental results are analyzed using two categories: normal and pathologic. By classifying the reduced features using the Support Vector Machine (SVM), 94% is achieved as classification accuracy. Compared to recent studies, the proposed expert system is extremely helpful and highly effective to resolve the problem of VNG analysis and provide an accurate diagnostic for medical devices.

Keywords: nystagmus, vestibular neuritis, videonystagmographic system, VNG, Fisher criterion, support vector machine, SVM

Procedia PDF Downloads 133
16216 Use of Fractal Geometry in Machine Learning

Authors: Fuad M. Alkoot

Abstract:

The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.

Keywords: fractal geometry, machine learning, classifier, fractal dimension

Procedia PDF Downloads 206
16215 A Bayesian Hierarchical Poisson Model with an Underlying Cluster Structure for the Analysis of Measles in Colombia

Authors: Ana Corberan-Vallet, Karen C. Florez, Ingrid C. Marino, Jose D. Bermudez

Abstract:

In 2016, the Region of the Americas was declared free of measles, a viral disease that can cause severe health problems. However, since 2017, measles has reemerged in Venezuela and has subsequently reached neighboring countries. In 2018, twelve American countries reported confirmed cases of measles. Governmental and health authorities in Colombia, a country that shares the longest land boundary with Venezuela, are aware of the need for a strong response to restrict the expanse of the epidemic. In this work, we apply a Bayesian hierarchical Poisson model with an underlying cluster structure to describe disease incidence in Colombia. Concretely, the proposed methodology provides relative risk estimates at the department level and identifies clusters of disease, which facilitates the implementation of targeted public health interventions. Socio-demographic factors, such as the percentage of migrants, gross domestic product, and entry routes, are included in the model to better describe the incidence of disease. Since the model does not impose any spatial correlation at any level of the model hierarchy, it avoids the spatial confounding problem and provides a suitable framework to estimate the fixed-effect coefficients associated with spatially-structured covariates.

Keywords: Bayesian analysis, cluster identification, disease mapping, risk estimation

Procedia PDF Downloads 148
16214 Effects of Active Muscle Contraction in a Car Occupant in Whiplash Injury

Authors: Nisha Nandlal Sharma, Julaluk Carmai, Saiprasit Koetniyom, Bernd Markert

Abstract:

Whiplash Injuries are usually associated with car accidents. The sudden forward or backward jerk to head causes neck strain, which is the result of damage to the muscle or tendons. Neck pain and headaches are the two most common symptoms of whiplash. Symptoms of whiplash are commonly reported in studies but the Injury mechanism is poorly understood. Neck muscles are the most important factor to study the neck Injury. This study focuses on the development of finite element (FE) model of human neck muscle to study the whiplash injury mechanism and effect of active muscle contraction on occupant kinematics. A detailed study of Injury mechanism will promote development and evaluation of new safety systems in cars, hence reducing the occurrence of severe injuries to the occupant. In present study, an active human finite element (FE) model with 3D neck muscle model is developed. Neck muscle was modeled with a combination of solid tetrahedral elements and 1D beam elements. Muscle active properties were represented by beam elements whereas, passive properties by solid tetrahedral elements. To generate muscular force according to inputted activation levels, Hill-type muscle model was applied to beam elements. To simulate non-linear passive properties of muscle, solid elements were modeled with rubber/foam material model. Material properties were assigned from published experimental tests. Some important muscles were then inserted into THUMS (Total Human Model for Safety) 50th percentile male pedestrian model. To reduce the simulation time required, THUMS lower body parts were not included. Posterior to muscle insertion, THUMS was given a boundary conditions similar to experimental tests. The model was exposed to 4g and 7g rear impacts as these load impacts are close to low speed impacts causing whiplash. The effect of muscle activation level on occupant kinematics during whiplash was analyzed.

Keywords: finite element model, muscle activation, neck muscle, whiplash injury prevention

Procedia PDF Downloads 354
16213 Influence of a Company’s Dynamic Capabilities on Its Innovation Capabilities

Authors: Lovorka Galetic, Zeljko Vukelic

Abstract:

The advanced concepts of strategic and innovation management in the sphere of company dynamic and innovation capabilities, and achieving their mutual alignment and a synergy effect, are important elements in business today. This paper analyses the theory and empirically investigates the influence of a company’s dynamic capabilities on its innovation capabilities. A new multidimensional model of dynamic capabilities is presented, consisting of five factors appropriate to real time requirements, while innovation capabilities are considered pursuant to the official OECD and Eurostat standards. After examination of dynamic and innovation capabilities indicated their theoretical links, the empirical study testing the model and examining the influence of a company’s dynamic capabilities on its innovation capabilities showed significant results. In the study, a research model was posed to relate company dynamic and innovation capabilities. One side of the model features the variables that are the determinants of dynamic capabilities defined through their factors, while the other side features the determinants of innovation capabilities pursuant to the official standards. With regard to the research model, five hypotheses were set. The study was performed in late 2014 on a representative sample of large and very large Croatian enterprises with a minimum of 250 employees. The research instrument was a questionnaire administered to company top management. For both variables, the position of the company was tested in comparison to industry competitors, on a fivepoint scale. In order to test the hypotheses, correlation tests were performed to determine whether there is a correlation between each individual factor of company dynamic capabilities with the existence of its innovation capabilities, in line with the research model. The results indicate a strong correlation between a company’s possession of dynamic capabilities in terms of their factors, due to the new multi-dimensional model presented in this paper, with its possession of innovation capabilities. Based on the results, all five hypotheses were accepted. Ultimately, it was concluded that there is a strong association between the dynamic and innovation capabilities of a company. 

Keywords: dynamic capabilities, innovation capabilities, competitive advantage, business results

Procedia PDF Downloads 299
16212 Machine Learning Methods for Flood Hazard Mapping

Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

Abstract:

This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

Procedia PDF Downloads 169
16211 Using SNAP and RADTRAD to Establish the Analysis Model for Maanshan PWR Plant

Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

Abstract:

In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation (RADTRAD), symbolic nuclear analysis package (SNAP), dose, PWR

Procedia PDF Downloads 452
16210 Mathematical Modeling of Drip Emitter Discharge of Trapezoidal Labyrinth Channel

Authors: N. Philipova

Abstract:

The influence of the geometric parameters of trapezoidal labyrinth channel on the emitter discharge is investigated in this work. The impact of the dentate angle, the dentate spacing, and the dentate height are studied among the geometric parameters of the labyrinth channel. Numerical simulations of the water flow movement are performed according to central cubic composite design using Commercial codes GAMBIT and FLUENT. Inlet pressure of the dripper is set up to be 1 bar. The objective of this paper is to derive a mathematical model of the emitter discharge depending on the dentate angle, the dentate spacing, the dentate height of the labyrinth channel. As a result, the obtained mathematical model is a second-order polynomial reporting 2-way interactions among the geometric parameters. The dentate spacing has the most important and positive influence on the emitter discharge, followed by the simultaneous impact of the dentate spacing and the dentate height. The dentate angle in the observed interval has no significant effect on the emitter discharge. The obtained model can be used as a basis for a future emitter design.

Keywords: drip irrigation, labyrinth channel hydrodynamics, numerical simulations, Reynolds stress model.

Procedia PDF Downloads 180
16209 Multiscale Cohesive Zone Modeling of Composite Microstructure

Authors: Vincent Iacobellis, Kamran Behdinan

Abstract:

A finite element cohesive zone model is used to predict the temperature dependent material properties of a polyimide matrix composite with unidirectional carbon fiber arrangement. The cohesive zone parameters have been obtained from previous research involving an atomistic-to-continuum multiscale simulation of the fiber-matrix interface using the bridging cell multiscale method. The goal of the research was to both investigate the effect of temperature change on the composite behavior with respect to transverse loading as well as the validate the use of cohesive parameters obtained from atomistic-to-continuum multiscale modeling to predict fiber-matrix interfacial cracking. From the multiscale model cohesive zone parameters (i.e. maximum traction and energy of separation) were obtained by modeling the interface between the coarse-grained polyimide matrix and graphite based carbon fiber. The cohesive parameters from this simulation were used in a cohesive zone model of the composite microstructure in order to predict the properties of the macroscale composite with respect to changes in temperature ranging from 21 ˚C to 316 ˚C. Good agreement was found between the microscale RUC model and experimental results for stress-strain response, stiffness, and material strength at low and high temperatures. Examination of the deformation of the composite through localized crack initiation at the fiber-matrix interface also agreed with experimental observations of similar phenomena. Overall, the cohesive zone model was shown to be both effective at modeling the composite properties with respect to transverse loading as well as validated the use of cohesive zone parameters obtained from the multiscale simulation.

Keywords: cohesive zone model, fiber-matrix interface, microscale damage, multiscale modeling

Procedia PDF Downloads 477
16208 Positive Obligations of the State Concerning the Protection of Human Rights

Authors: Monika Florczak-Wator

Abstract:

The model of positive obligations of the state concerning the protection of the rights of an individual was created within the jurisdiction of the German Federal Constitutional Court in the 1970s. That model assumes that the state should protect an individual against infringement of their fundamental rights by another individual. It is based on the idea concerning the modification of the function and duties of the state towards an individual and society. Initially the state was perceived as the main infringer of the fundamental rights of an individual formulating the individual’s obligations of negative nature (obligation of noninterference), however, at present the state is perceived as a guarantor and protector of the fundamental rights of an individual of positive nature (obligation of protection). Examination of the chosen judicial decisions of that court will enable us to determine what the obligation of protection is specifically about, when it is updated and whether it is accompanied by claims of an individual requesting the state to take actions protecting their fundamental rights against infringement by the private entities. The comparative perspective for the German model of positive obligations of the state will be an analogous model present in the jurisdiction of the European Court of Human Rights. It is justified to include it in the research as the Convention, similarly to the constitution, focuses on the protection of an individual against the infringement of their rights by the state and both models have been developed within the jurisdiction for several dozens of years. Analysis of the provisions of the Constitution of the Republic of Poland as well as judgements of the Polish Constitutional Tribunal will allow for the presentation of the application the model of the protective duties of the state in Poland.

Keywords: human rights, horizontal relationships, constitution, state protection

Procedia PDF Downloads 478
16207 Downscaling Daily Temperature with Neuroevolutionary Algorithm

Authors: Min Shi

Abstract:

State of the art research with Artificial Neural Networks for the downscaling of General Circulation Models (GCMs) mainly uses back-propagation algorithm as a training approach. This paper introduces another training approach of ANNs, Evolutionary Algorithm. The combined algorithm names neuroevolutionary (NE) algorithm. We investigate and evaluate the use of the NE algorithms in statistical downscaling by generating temperature estimates at interior points given information from a lattice of surrounding locations. The results of our experiments indicate that NE algorithms can be efficient alternative downscaling methods for daily temperatures.

Keywords: temperature, downscaling, artificial neural networks, evolutionary algorithms

Procedia PDF Downloads 344
16206 The Use of Hec Ras One-Dimensional Model and Geophysics for the Determination of Flood Zones

Authors: Ayoub El Bourtali, Abdessamed Najine, Amrou Moussa Benmoussa

Abstract:

It is becoming more and more necessary to manage flood risk, and it must include all stakeholders and all possible means available. The goal of this work is to map the vulnerability of the Oued Derna-region Tagzirt flood zone in the semi-arid region. This is about implementing predictive models and flood control. This allows for the development of flood risk prevention plans. In this study, A resistivity survey was conducted over the area to locate and evaluate soil characteristics in order to calculate discharges and prevent flooding for the study area. The development of a one-dimensional (1D) hydrodynamic model of the Derna River was carried out in HEC-RAS 5.0.4 using a combination of survey data and spatially extracted cross-sections and recorded river flows. The study area was hit by several extreme floods, causing a lot of property loss and loss of life. This research focuses on the most recent flood events, based on the collected data, the water level, river flow and river cross-section were analyzed. A set of flood levels were obtained as the outputs of the hydraulic model and the accuracy of the simulated flood levels and velocity.

Keywords: derna river, 1D hydrodynamic model, flood modelling, HEC-RAS 5.0.4

Procedia PDF Downloads 304
16205 Comparison of Two-Phase Critical Flow Models for Estimation of Leak Flow Rate through Cracks

Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano

Abstract:

The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.

Keywords: crack, critical flow, leak, roughness

Procedia PDF Downloads 173
16204 A Modelling Study of the Photochemical and Particulate Pollution Characteristics above a Typical Southeast Mediterranean Urban Area

Authors: Fameli Kyriaki-Maria, Assimakopoulos D. Vasiliki, Kotroni Vassiliki

Abstract:

The Greater Athens Area (GAA) faces photochemical and particulate pollution episodes as a result of the combined effects of local pollutant emissions, regional pollution transport, synoptic circulation and topographic characteristics. The area has undergone significant changes since the Athens 2004 Olympic Games because of large scale infrastructure works that lead to the shift of population to areas previously characterized as rural, the increase of the traffic fleet and the operation of highways. However, no recent modelling studies have been performed due to the lack of an accurate, updated emission inventory. The photochemical modelling system MM5/CAMx was applied in order to study the photochemical and particulate pollution characteristics above the GAA for two distinct ten-day periods in the summer of 2006 and 2010, where air pollution episodes occurred. A new updated emission inventory was used based on official data. Comparison of modeled results with measurements revealed the importance and accuracy of the new Athens emission inventory as compared to previous modeling studies. The model managed to reproduce the local meteorological conditions, the daily ozone and particulates fluctuations at different locations across the GAA. Higher ozone levels were found at suburban and rural areas as well as over the sea at the south of the basin. Concerning PM10, high concentrations were computed at the city centre and the southeastern suburbs in agreement with measured data. Source apportionment analysis showed that different sources contribute to the ozone levels, the local sources (traffic, port activities) affecting its formation.

Keywords: photochemical modelling, urban pollution, greater Athens area, MM5/CAMx

Procedia PDF Downloads 277
16203 A Development of Science Instructional Model Based on Stem Education Approach to Enhance Scientific Mind and Problem Solving Skills for Primary Students

Authors: Prasita Sooksamran, Wareerat Kaewurai

Abstract:

STEM is an integrated teaching approach promoted by the Ministry of Education in Thailand. STEM Education is an integrated approach to teaching Science, Technology, Engineering, and Mathematics. It has been questioned by Thai teachers on the grounds of how to integrate STEM into the classroom. Therefore, the main objective of this study is to develop a science instructional model based on the STEM approach to enhance scientific mind and problem-solving skills for primary students. This study is participatory action research, and follows the following steps: 1) develop a model 2) seek the advice of experts regarding the teaching model. Developing the instructional model began with the collection and synthesis of information from relevant documents, related research and other sources in order to create prototype instructional model. 2) The examination of the validity and relevance of instructional model by a panel of nine experts. The findings were as follows: 1. The developed instructional model comprised of principles, objective, content, operational procedures and learning evaluation. There were 4 principles: 1) Learning based on the natural curiosity of primary school level children leading to knowledge inquiry, understanding and knowledge construction, 2) Learning based on the interrelation between people and environment, 3) Learning that is based on concrete learning experiences, exploration and the seeking of knowledge, 4) Learning based on the self-construction of knowledge, creativity, innovation and 5) relating their findings to real life and the solving of real-life problems. The objective of this construction model is to enhance scientific mind and problem-solving skills. Children will be evaluated according to their achievements. Lesson content is based on science as a core subject which is integrated with technology and mathematics at grade 6 level according to The Basic Education Core Curriculum 2008 guidelines. The operational procedures consisted of 6 steps: 1) Curiosity 2) Collection of data 3) Collaborative planning 4) Creativity and Innovation 5) Criticism and 6) Communication and Service. The learning evaluation is an authentic assessment based on continuous evaluation of all the material taught. 2. The experts agreed that the Science Instructional Model based on the STEM Education Approach had an excellent level of validity and relevance (4.67 S.D. 0.50).

Keywords: instructional model, STEM education, scientific mind, problem solving

Procedia PDF Downloads 187
16202 Advanced Structural Analysis of Energy Storage Materials

Authors: Disha Gupta

Abstract:

The aim of this research is to conduct X-ray and e-beam characterization techniques on lithium-ion battery materials for the improvement of battery performance. The key characterization techniques employed are the synchrotron X-ray Absorption Spectroscopy (XAS) combined with X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to obtain a more holistic approach to understanding material properties. This research effort provides additional battery characterization knowledge that promotes the development of new cathodes, anodes, electrolyte and separator materials for batteries, hence, leading to better and more efficient battery performance. Both ex-situ and in-situ synchrotron experiments were performed on LiFePO₄, one of the most common cathode material, from different commercial sources and their structural analysis, were conducted using Athena/Artemis software. This analysis technique was then further extended to study other cathode materials like LiMnxFe(₁₋ₓ)PO₄ and even some sulphate systems like Li₂Mn(SO₄)₂ and Li₂Co0.5Mn₀.₅ (SO₄)₂. XAS data were collected for Fe and P K-edge for LiFePO4, and Fe, Mn and P-K-edge for LiMnxFe(₁₋ₓ)PO₄ to conduct an exhaustive study of the structure. For the sulphate system, Li₂Mn(SO₄)₂, XAS data was collected at both Mn and S K-edge. Finite Difference Method for Near Edge Structure (FDMNES) simulations were also conducted for various iron, manganese and phosphate model compounds and compared with the experimental XANES data to understand mainly the pre-edge structural information of the absorbing atoms. The Fe K-edge XAS results showed a charge compensation occurring on the Fe atom for all the differently synthesized LiFePO₄ materials as well as the LiMnxFe(₁₋ₓ)PO₄ systems. However, the Mn K-edge showed a difference in results as the Mn concentration changed in the materials. For the sulphate-based system Li₂Mn(SO₄)₂, however, no change in the Mn K-edge was observed, even though electrochemical studies showed Mn redox reactions.

Keywords: li-ion batteries, electrochemistry, X-ray absorption spectroscopy, XRD

Procedia PDF Downloads 145
16201 Damage-Based Seismic Design and Evaluation of Reinforced Concrete Bridges

Authors: Ping-Hsiung Wang, Kuo-Chun Chang

Abstract:

There has been a common trend worldwide in the seismic design and evaluation of bridges towards the performance-based method where the lateral displacement or the displacement ductility of bridge column is regarded as an important indicator for performance assessment. However, the seismic response of a bridge to an earthquake is a combined result of cyclic displacements and accumulated energy dissipation, causing damage to the bridge, and hence the lateral displacement (ductility) alone is insufficient to tell its actual seismic performance. This study aims to propose a damage-based seismic design and evaluation method for reinforced concrete bridges on the basis of the newly developed capacity-based inelastic displacement spectra. The capacity-based inelastic displacement spectra that comprise an inelastic displacement ratio spectrum and a corresponding damage state spectrum was constructed by using a series of nonlinear time history analyses and a versatile, smooth hysteresis model. The smooth model could take into account the effects of various design parameters of RC bridge columns and correlates the column’s strength deterioration with the Park and Ang’s damage index. It was proved that the damage index not only can be used to accurately predict the onset of strength deterioration, but also can be a good indicator for assessing the actual visible damage condition of column regardless of its loading history (i.e., similar damage index corresponds to similar actual damage condition for the same designed columns subjected to very different cyclic loading protocols as well as earthquake loading), providing a better insight into the seismic performance of bridges. Besides, the computed spectra show that the inelastic displacement ratio for far-field ground motions approximately conforms to the equal displacement rule when structural period is larger than around 0.8 s, but that for near-fault ground motions departs from the rule in the whole considered spectral regions. Furthermore, the near-fault ground motions would lead to significantly greater inelastic displacement ratio and damage index than far-field ground motions and most of the practical design scenarios cannot survive the considered near-fault ground motion when the strength reduction factor of bridge is not less than 5.0. Finally, the spectrum formula is presented as a function of structural period, strength reduction factor, and various column design parameters for far-field and near-fault ground motions by means of the regression analysis of the computed spectra. And based on the developed spectrum formula, a design example of a bridge is presented to illustrate the proposed damage-based seismic design and evaluation method where the damage state of the bridge is used as the performance objective.

Keywords: damage index, far-field, near-fault, reinforced concrete bridge, seismic design and evaluation

Procedia PDF Downloads 120
16200 Forecasting Container Throughput: Using Aggregate or Terminal-Specific Data?

Authors: Gu Pang, Bartosz Gebka

Abstract:

We forecast the demand of total container throughput at the Indonesia’s largest seaport, Tanjung Priok Port. We propose four univariate forecasting models, including SARIMA, the additive Seasonal Holt-Winters, the multiplicative Seasonal Holt-Winters and the Vector Error Correction Model. Our aim is to provide insights into whether forecasting the total container throughput obtained by historical aggregated port throughput time series is superior to the forecasts of the total throughput obtained by summing up the best individual terminal forecasts. We test the monthly port/individual terminal container throughput time series between 2003 and 2013. The performance of forecasting models is evaluated based on Mean Absolute Error and Root Mean Squared Error. Our results show that the multiplicative Seasonal Holt-Winters model produces the most accurate forecasts of total container throughput, whereas SARIMA generates the worst in-sample model fit. The Vector Error Correction Model provides the best model fits and forecasts for individual terminals. Our results report that the total container throughput forecasts based on modelling the total throughput time series are consistently better than those obtained by combining those forecasts generated by terminal-specific models. The forecasts of total throughput until the end of 2018 provide an essential insight into the strategic decision-making on the expansion of port's capacity and construction of new container terminals at Tanjung Priok Port.

Keywords: SARIMA, Seasonal Holt-Winters, Vector Error Correction Model, container throughput

Procedia PDF Downloads 497
16199 Predicting the Exposure Level of Airborne Contaminants in Occupational Settings via the Well-Mixed Room Model

Authors: Alireza Fallahfard, Ludwig Vinches, Stephane Halle

Abstract:

In the workplace, the exposure level of airborne contaminants should be evaluated due to health and safety issues. It can be done by numerical models or experimental measurements, but the numerical approach can be useful when it is challenging to perform experiments. One of the simplest models is the well-mixed room (WMR) model, which has shown its usefulness to predict inhalation exposure in many situations. However, since the WMR is limited to gases and vapors, it cannot be used to predict exposure to aerosols. The main objective is to modify the WMR model to expand its application to exposure scenarios involving aerosols. To reach this objective, the standard WMR model has been modified to consider the deposition of particles by gravitational settling and Brownian and turbulent deposition. Three deposition models were implemented in the model. The time-dependent concentrations of airborne particles predicted by the model were compared to experimental results conducted in a 0.512 m3 chamber. Polystyrene particles of 1, 2, and 3 µm in aerodynamic diameter were generated with a nebulizer under two air changes per hour (ACH). The well-mixed condition and chamber ACH were determined by the tracer gas decay method. The mean friction velocity on the chamber surfaces as one of the input variables for the deposition models was determined by computational fluid dynamics (CFD) simulation. For the experimental procedure, the particles were generated until reaching the steady-state condition (emission period). Then generation stopped, and concentration measurements continued until reaching the background concentration (decay period). The results of the tracer gas decay tests revealed that the ACHs of the chamber were: 1.4 and 3.0, and the well-mixed condition was achieved. The CFD results showed the average mean friction velocity and their standard deviations for the lowest and highest ACH were (8.87 ± 0.36) ×10-2 m/s and (8.88 ± 0.38) ×10-2 m/s, respectively. The numerical results indicated the difference between the predicted deposition rates by the three deposition models was less than 2%. The experimental and numerical aerosol concentrations were compared in the emission period and decay period. In both periods, the prediction accuracy of the modified model improved in comparison with the classic WMR model. However, there is still a difference between the actual value and the predicted value. In the emission period, the modified WMR results closely follow the experimental data. However, the model significantly overestimates the experimental results during the decay period. This finding is mainly due to an underestimation of the deposition rate in the model and uncertainty related to measurement devices and particle size distribution. Comparing the experimental and numerical deposition rates revealed that the actual particle deposition rate is significant, but the deposition mechanisms considered in the model were ten times lower than the experimental value. Thus, particle deposition was significant and will affect the airborne concentration in occupational settings, and it should be considered in the airborne exposure prediction model. The role of other removal mechanisms should be investigated.

Keywords: aerosol, CFD, exposure assessment, occupational settings, well-mixed room model, zonal model

Procedia PDF Downloads 96
16198 Comparison Approach for Wind Resource Assessment to Determine Most Precise Approach

Authors: Tasir Khan, Ishfaq Ahmad, Yejuan Wang, Muhammad Salam

Abstract:

Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy.

Keywords: wind-speed modeling, goodness of fit, maximum likelihood method, linear moment

Procedia PDF Downloads 81
16197 Fault Diagnosis in Induction Motor

Authors: Kirti Gosavi, Anita Bhole

Abstract:

The paper demonstrates simulation and steady-state performance of three phase squirrel cage induction motor and detection of rotor broken bar fault using MATLAB. This simulation model is successfully used in the fault detection of rotor broken bar for the induction machines. A dynamic model using PWM inverter and mathematical modelling of the motor is developed. The dynamic simulation of the small power induction motor is one of the key steps in the validation of the design process of the motor drive system and it is needed for eliminating advertent design errors and the resulting error in the prototype construction and testing. The simulation model will be helpful in detecting the faults in three phase induction motor using Motor current signature analysis.

Keywords: squirrel cage induction motor, pulse width modulation (PWM), fault diagnosis, induction motor

Procedia PDF Downloads 624
16196 Rapid Assessment the Ability of Forest Vegetation in Kulonprogo to Store Carbon Using Multispectral Satellite Imagery and Vegetation Index

Authors: Ima Rahmawati, Nur Hafizul Kalam

Abstract:

Development of industrial and economic sectors in various countries very rapidly caused raising the greenhouse gas (GHG) emissions. Greenhouse gases are dominated by carbon dioxide (CO2) and methane (CH4) in the atmosphere that make the surface temperature of the earth always increase. The increasing gases caused by incomplete combustion of fossil fuels such as petroleum and coals and also high rate of deforestation. Yogyakarta Special Province which every year always become tourist destination, has a great potency in increasing of greenhouse gas emissions mainly from the incomplete combustion. One of effort to reduce the concentration of gases in the atmosphere is keeping and empowering the existing forests in the Province of Yogyakarta, especially forest in Kulonprogro is to be maintained the greenness so that it can absorb and store carbon maximally. Remote sensing technology can be used to determine the ability of forests to absorb carbon and it is connected to the density of vegetation. The purpose of this study is to determine the density of the biomass of forest vegetation and determine the ability of forests to store carbon through Photo-interpretation and Geographic Information System approach. Remote sensing imagery that used in this study is LANDSAT 8 OLI year 2015 recording. LANDSAT 8 OLI imagery has 30 meters spatial resolution for multispectral bands and it can give general overview the condition of the carbon stored from every density of existing vegetation. The method is the transformation of vegetation index combined with allometric calculation of field data then doing regression analysis. The results are model maps of density and capability level of forest vegetation in Kulonprogro, Yogyakarta in storing carbon.

Keywords: remote sensing, carbon, kulonprogo, forest vegetation, vegetation index

Procedia PDF Downloads 390
16195 The Effect of Foundation on the Earth Fill Dam Settlement

Authors: Masoud Ghaemi, Mohammadjafar Hedayati, Faezeh Yousefzadeh, Hoseinali Heydarzadeh

Abstract:

Careful monitoring in the earth dams to measure deformation caused by settlement and movement has always been a concern for engineers in the field. In order to measure settlement and deformation of earth dams, usually, the precision instruments of settlement set and combined Inclinometer that is commonly referred to IS instrument will be used. In some dams, because the thickness of alluvium is high and there is no possibility of alluvium removal (technically and economically and in terms of performance), there is no possibility of placing the end of IS instrument (precision instruments of Inclinometer-settlement set) in the rock foundation. Inevitably, have to accept installing pipes in the weak and deformable alluvial foundation that leads to errors in the calculation of the actual settlement (absolute settlement) in different parts of the dam body. The purpose of this paper is to present new and refine criteria for predicting settlement and deformation in earth dams. The study is based on conditions in three dams with a deformation quite alluvial (Agh Chai, Narmashir and Gilan-e Gharb) to provide settlement criteria affected by the alluvial foundation. To achieve this goal, the settlement of dams was simulated by using the finite difference method with FLAC3D software, and then the modeling results were compared with the reading IS instrument. In the end, the caliber of the model and validate the results, by using regression analysis techniques and scrutinized modeling parameters with real situations and then by using MATLAB software and CURVE FITTING toolbox, new criteria for the settlement based on elasticity modulus, cohesion, friction angle, the density of earth dam and the alluvial foundation was obtained. The results of these studies show that, by using the new criteria measures, the amount of settlement and deformation for the dams with alluvial foundation can be corrected after instrument readings, and the error rate in reading IS instrument can be greatly reduced.

Keywords: earth-fill dam, foundation, settlement, finite difference, MATLAB, curve fitting

Procedia PDF Downloads 187
16194 Geometrically Linear Symmetric Free Vibration Analysis of Sandwich Beam

Authors: Ibnorachid Zakaria, El Bikri Khalid, Benamar Rhali, Farah Abdoun

Abstract:

The aim of the present work is to study the linear free symmetric vibration of three-layer sandwich beam using the energy method. The zigzag model is used to describe the displacement field. The theoretical model is based on the top and bottom layers behave like Euler-Bernoulli beams while the core layer like a Timoshenko beam. Based on Hamilton’s principle, the governing equation of motion sandwich beam is obtained in order to calculate the linear frequency parameters for a clamped-clamped and simple supported-simple-supported beams. The effects of material properties and geometric parameters on the natural frequencies are also investigated.

Keywords: linear vibration, sandwich, shear deformation, Timoshenko zig-zag model

Procedia PDF Downloads 467