Search results for: lumped thermal model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19311

Search results for: lumped thermal model

16191 The Impact of Bequest Taxation on Human Capital Accumulation

Authors: Maciej Dudek, Robert Kruszewski, Janusz Kudla, Konrad Walczyk

Abstract:

In this paper, we study how taxation of bequests affects human capital formation in the long term and short term horizon. Our underlying model is an overlapping generation model (OLG) with some degree of altruism on the part of the ancestors' generation towards their descendants. We ask the question in three separate frameworks. First, we study a simple one-sector model where a proxy of human capital is wage income. It the steady-state -for CRRA utility function and human capital produced with non-decreasing returns -the taxation of bequests is neutral to the accumulation of human capital. In the second framework, neutrality applies to the growth rates of human capital, physical capital, and consumption. In this case, taxation increases the level of bequests, leading to a lower value of current consumption. Finally in we consider two periods model instead of infinite horizon model as long as the tax revenue is at least partially rebated back to the public, the fraction of human capital engaged in the process of formation of human capital increases with the tax rate on bequests. In other words, taxation of bequests is partially offset by an increase in human capital formation. Higher human capital allows the future generation to earn higher wages, and today's generation can find it optimal to endow the future generation with more human capital when taxation is imposed on physical capital transferred to the next generation.

Keywords: taxation, bequests, policy, human capital

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16190 Immobilization of β-Galactosidase from Kluyveromyces Lactis on Polyethylenimine-Agarose for Production of Lactulose

Authors: Carlos A. C. G. Neto, Natan C. G. Silva, Thais O. Costa, Luciana R. B. Goncalves, Maria v. P. Rocha

Abstract:

Galactosidases are enzymes responsible for catalyzing lactose hydrolysis reactions and also favoring transgalactosylation reactions for the production of prebiotics, among which lactulose stands out. These enzymes, when immobilized, can have some enzymatic characteristics substantially improved, and the coating of supports with multifunctional polymers in immobilization processes is a promising alternative in order to extend the useful life of the biocatalysts, for example, the coating with polyethyleneimine (PEI). PEI is a flexible polymer that suits the structure of the enzyme, giving greater stability, especially for multimeric enzymes such as β-galactosidases and also protects it from environmental variations, for example, pH and temperature. In addition, it can substantially improve the immobilization parameters and also the efficiency of enzymatic reactions. In this context, the aim of the present work was first to develop biocatalysts of β-galactosidase from Kluyveromyces lactis immobilized on PEI coated agarose, determining the immobilization parameters, its operational and thermal stability, and then to apply it in the hydrolysis of lactose and synthesis of lactulose, using whey as a substrate. This immobilization strategy was chosen in order to improve the catalytic efficiency of the enzyme in the transgalactosylation reaction for the production of prebiotics, and there are few studies with β-galactosidase from this strain. The immobilization of β-galactosidase in agarose previously functionalized with 48% (w/v) glycidol and then coated with 10% (w/v) PEI solution was evaluated using an enzymatic load of 10 mg/g of protein. Subsequently, the hydrolysis and transgalactosylation reactions were conducted at 50 °C, 120 RPM for 20 minutes, using whey (66.7 g/L of lactose) supplemented with 133.3 g/L fructose at a ratio of 1:2 (lactose/fructose). Operational stability studies were performed in the same conditions for 10 cycles. Thermal stabilities of biocatalysts were conducted at 50 ºC in 50 mM phosphate buffer, pH 6.6, with 0.1 mM MnCl2. The biocatalysts whose supports were coated were named AGA_GLY_PEI_GAL, and those that were not coated were named AGA_GLY_GAL. The coating of the support with PEI considerably improved immobilization yield (2.6-fold), the biocatalyst activity (1.4-fold), and efficiency (2.2-fold). The biocatalyst AGA_GLY_PEI_GAL was better than AGA_GLY_GAL in hydrolysis and transgalactosylation reactions, converting 88.92% of lactose at 5 min of reaction and obtaining a residual concentration of 5.24 g/L. Besides that, it was produced 13.90 g/L lactulose in the same time interval. AGA_GLY_PEI_GAL biocatalyst was stable during the 10 cycles evaluated, converting approximately 80% of lactose and producing 10.95 g/L of lactulose even after the tenth cycle. However, the thermal stability of AGA_GLY_GAL biocatalyst was superior, with a half-life time 5 times higher, probably because the enzyme was immobilized by covalent bonding, which is stronger than adsorption (AGA_GLY_PEI_GAL). Therefore, the strategy of coating the supports with PEI has proven to be effective for the immobilization of β-galactosidase from K. lactis, considerably improving the immobilization parameters, as well as the enzyme, catalyzed reactions. In addition, the use of whey as a raw material for lactulose production has proved to be an industrially advantageous alternative.

Keywords: β-galactosidase, immobilization, lactulose, polyethylenimine, whey

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16189 Structural Damage Detection Using Modal Data Employing Teaching Learning Based Optimization

Authors: Subhajit Das, Nirjhar Dhang

Abstract:

Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

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16188 Role of Microplastics on Reducing Heavy Metal Pollution from Wastewater

Authors: Derin Ureten

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Plastic pollution does not disappear, it gets smaller and smaller through photolysis which are caused mainly by sun’s radiation, thermal oxidation, thermal degradation, and biodegradation which is the action of organisms digesting larger plastics. All plastic pollutants have exceedingly harmful effects on the environment. Together with the COVID-19 pandemic, the number of plastic products such as masks and gloves flowing into the environment has increased more than ever. However, microplastics are not the only pollutants in water, one of the most tenacious and toxic pollutants are heavy metals. Heavy metal solutions are also capable of causing varieties of health problems in organisms such as cancer, organ damage, nervous system damage, and even death. The aim of this research is to prove that microplastics can be used in wastewater treatment systems by proving that they could adsorb heavy metals in solutions. Experiment for this research will include two heavy metal solutions; one including microplastics in a heavy metal contaminated water solution, and one that just includes heavy metal solution. After being sieved, absorbance of both mediums will be measured with the help of a spectrometer. Iron (III) chloride (FeCl3) will be used as the heavy metal solution since the solution becomes darker as the presence of this substance increases. The experiment will be supported by Pure Nile Red powder in order to observe if there are any visible differences under the microscope. Pure Nile Red powder is a chemical that binds to hydrophobic materials such as plastics and lipids. If proof of adsorbance could be observed by the rates of the solutions' final absorbance rates and visuals ensured by the Pure Nile Red powder, the experiment will be conducted with different temperature levels in order to analyze the most accurate temperature level to proceed with removal of heavy metals from water. New wastewater treatment systems could be generated with the help of microplastics, for water contaminated with heavy metals.

Keywords: microplastics, heavy metal, pollution, adsorbance, wastewater treatment

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16187 Elaboration and Investigation of the New Ecologically Clean Friction Composite Materials on the Basis of Nanoporous Raw Materials

Authors: Lia Gventsadze, Elguja Kutelia, David Gventsadze

Abstract:

The purpose of the article is to show the possibility for the development of a new generation, eco-friendly (asbestos free) nano-porous friction materials on the basis of Georgian raw materials, along with the determination of technological parameters for their production, as well as the optimization of tribological properties and the investigation of structural aspects of wear peculiarities of elaborated materials using the scanning electron microscopy (SEM) and Auger electron spectroscopy (AES) methods. The study investigated the tribological properties of the polymer friction materials on the basis of the phenol-formaldehyde resin using the porous diatomite filler modified by silane with the aim to improve the thermal stability, while the composition was modified by iron phosphate, technical carbon and basalt fibre. As a result of testing the stable values of friction factor (0.3-0,45) were reached, both in dry and wet friction conditions, the friction working parameters (friction factor and wear stability) remained stable up to 500 OC temperatures, the wear stability of gray cast-iron disk increased 3-4 times, the soundless operation of materials without squeaking were achieved. Herewith it was proved that small amount of ingredients (5-6) are enough to compose the nano-porous friction materials. The study explains the mechanism of the action of nano-porous composition base brake lining materials and its tribological efficiency on the basis of the triple phase model of the tribo-pair.

Keywords: brake lining, friction coefficient, wear, nanoporous composite, phenolic resin

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16186 Microwave Dielectric Relaxation Study of Diethanolamine with Triethanolamine from 10 MHz-20 GHz

Authors: A. V. Patil

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The microwave dielectric relaxation study of diethanolamine with triethanolamine binary mixture have been determined over the frequency range of 10 MHz to 20 GHz, at various temperatures using time domain reflectometry (TDR) method for 11 concentrations of the system. The present work reveals molecular interaction between same multi-functional groups [−OH and –NH2] of the alkanolamines (diethanolamine and triethanolamine) using different models such as Debye model, Excess model, and Kirkwood model. The dielectric parameters viz. static dielectric constant (ε0) and relaxation time (τ) have been obtained with Debye equation characterized by a single relaxation time without relaxation time distribution by the least squares fit method.

Keywords: diethanolamine, excess properties, kirkwood properties, time domain reflectometry, triethanolamine

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16185 Performance Evaluation of the Classic seq2seq Model versus a Proposed Semi-supervised Long Short-Term Memory Autoencoder for Time Series Data Forecasting

Authors: Aswathi Thrivikraman, S. Advaith

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The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

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16184 Hierarchical Tree Long Short-Term Memory for Sentence Representations

Authors: Xiuying Wang, Changliang Li, Bo Xu

Abstract:

A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

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16183 'Gender' and 'Gender Equalities': Conceptual Issues

Authors: Moustafa Ali

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The aim of this paper is to discuss and question some of the widely accepted concepts within the conceptual framework of gender from terminological, scientific, and Muslim cultural perspectives, and to introduce a new definition and a model of gender in the Arab and Muslim societies. This paper, therefore, uses a generic methodology and document analysis and comes in three sections and a conclusion. The first section discusses some of the terminological issues in the conceptual framework of gender. The second section highlights scientific issues, introduces a definition and a model of gender, whereas the third section offers Muslim cultural perspectives on some issues related to gender in the Muslim world. The paper, then, concludes with findings and recommendations reached so far.

Keywords: gender definition, gender equalities, sex-gender separability, fairness-based model of gender

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16182 A Mathematical Programming Model for Lot Sizing and Production Planning in Multi-Product Companies: A Case Study of Azar Battery Company

Authors: Farzad Jafarpour Taher, Maghsud Solimanpur

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Production planning is one of the complex tasks in multi-product firms that produce a wide range of products. Since resources in mass production companies are limited and different products use common resources, there must be a careful plan so that firms can respond to customer needs efficiently. Azar-battery Company is a firm that provides twenty types of products for its customers. Therefore, careful planning must be performed in this company. In this research, the current conditions of Azar-battery Company were investigated to provide a mathematical programming model to determine the optimum production rate of the products in this company. The production system of this company is multi-stage, multi-product and multi-period. This system is studied in terms of a one-year planning horizon regarding the capacity of machines and warehouse space limitation. The problem has been modeled as a linear programming model with deterministic demand in which shortage is not allowed. The objective function of this model is to minimize costs (including raw materials, assembly stage, energy costs, packaging, and holding). Finally, this model has been solved by Lingo software using the branch and bound approach. Since the computation time was very long, the solver interrupted, and the obtained feasible solution was used for comparison. The proposed model's solution costs have been compared to the company’s real data. This non-optimal solution reduces the total production costs of the company by about %35.

Keywords: multi-period, multi-product production, multi-stage, production planning

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16181 Flexible PVC Based Nanocomposites With the Incorporation of Electric and Magnetic Nanofillers for the Shielding Against EMI and Thermal Imaging Signals

Authors: H. M. Fayzan Shakir, Khadija Zubair, Tingkai Zhao

Abstract:

Electromagnetic (EM) waves are being used widely now a days. Cell phone signals, WIFI signals, wireless telecommunications etc everything uses EM waves which then create EM pollution. EM pollution can cause serious effects on both human health and nearby electronic devices. EM waves have electric and magnetic components that disturb the flow of charged particles in both human nervous system and electronic devices. The shielding of both humans and electronic devices are a prime concern today. EM waves can cause headaches, anxiety, suicide and depression, nausea, fatigue and loss of libido in humans and malfunctioning in electronic devices. Polyaniline (PANI) and polypyrrole (PPY) were successfully synthesized using chemical polymerizing using ammonium persulfate and DBSNa as oxidant respectively. Barium ferrites (BaFe) were also prepared using co-precipitation method and calcinated at 10500C for 8h. Nanocomposite thin films with various combinations and compositions of Polyvinylchloride, PANI, PPY and BaFe were prepared. X-ray diffraction technique was first used to confirm the successful fabrication of all nano fillers and particle size analyzer to measure the exact size and scanning electron microscopy is used for the shape. According to Electromagnetic Interference theory, electrical conductivity is the prime property required for the Electromagnetic Interference shielding. 4-probe technique is then used to evaluate DC conductivity of all samples. Samples with high concentration of PPY and PANI exhibit remarkable increased electrical conductivity due to fabrication of interconnected network structure inside the Polyvinylchloride matrix that is also confirmed by SEM analysis. Less than 1% transmission was observed in whole NIR region (700 nm – 2500 nm). Also, less than -80 dB Electromagnetic Interference shielding effectiveness was observed in microwave region (0.1 GHz to 20 GHz).

Keywords: nanocomposites, polymers, EMI shielding, thermal imaging

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16180 Logistics Model for Improving Quality in Railway Transport

Authors: Eva Nedeliakova, Juraj Camaj, Jaroslav Masek

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This contribution is focused on the methodology for identifying levels of quality and improving quality through new logistics model in railway transport. It is oriented on the application of dynamic quality models, which represent an innovative method of evaluation quality services. Through this conception, time factor, expected, and perceived quality in each moment of the transportation process within logistics chain can be taken into account. Various models describe the improvement of the quality which emphases the time factor throughout the whole transportation logistics chain. Quality of services in railway transport can be determined by the existing level of service quality, by detecting the causes of dissatisfaction employees but also customers, to uncover strengths and weaknesses. This new logistics model is able to recognize critical processes in logistic chain. It includes service quality rating that must respect its specific properties, which are unrepeatability, impalpability, their use right at the time they are provided and particularly changeability, which is significant factor in the conditions of rail transport as well. These peculiarities influence the quality of service regarding the constantly increasing requirements and that result in new ways of finding progressive attitudes towards the service quality rating.

Keywords: logistics model, quality, railway transport

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16179 Simple Multiple-Attribute Rating Technique for Optimal Decision-Making Model on Selecting Best Spiker of World Grand Prix

Authors: Chen Chih-Cheng, Chen I-Cheng, Lee Yung-Tan, Kuo Yen-Whea, Yu Chin-Hung

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The purpose of this study is to construct a model for best spike player selection in a top volleyball tournament of the world. Data consisted of the records of 2013 World Grand Prix declared by International Volleyball Federation (FIVB). Simple Multiple-Attribute Rating Technique (SMART) was used for optimal decision-making model on the best spike player selection. The research results showed that the best spike player ranking by SMART is different than the ranking by FIVB. The results demonstrated the effectiveness and feasibility of the proposed model.

Keywords: simple multiple-attribute rating technique, World Grand Prix, best spike player, International Volleyball Federation

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16178 An Experimental Study on Some Conventional and Hybrid Models of Fuzzy Clustering

Authors: Jeugert Kujtila, Kristi Hoxhalli, Ramazan Dalipi, Erjon Cota, Ardit Murati, Erind Bedalli

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Clustering is a versatile instrument in the analysis of collections of data providing insights of the underlying structures of the dataset and enhancing the modeling capabilities. The fuzzy approach to the clustering problem increases the flexibility involving the concept of partial memberships (some value in the continuous interval [0, 1]) of the instances in the clusters. Several fuzzy clustering algorithms have been devised like FCM, Gustafson-Kessel, Gath-Geva, kernel-based FCM, PCM etc. Each of these algorithms has its own advantages and drawbacks, so none of these algorithms would be able to perform superiorly in all datasets. In this paper we will experimentally compare FCM, GK, GG algorithm and a hybrid two-stage fuzzy clustering model combining the FCM and Gath-Geva algorithms. Firstly we will theoretically dis-cuss the advantages and drawbacks for each of these algorithms and we will describe the hybrid clustering model exploiting the advantages and diminishing the drawbacks of each algorithm. Secondly we will experimentally compare the accuracy of the hybrid model by applying it on several benchmark and synthetic datasets.

Keywords: fuzzy clustering, fuzzy c-means algorithm (FCM), Gustafson-Kessel algorithm, hybrid clustering model

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16177 The Development of Directed-Project Based Learning as Language Learning Model to Improve Students' English Achievement

Authors: Tri Pratiwi, Sufyarma Marsidin, Hermawati Syarif, Yahya

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The 21st-century skills being highly promoted today are Creativity and Innovation, Critical Thinking and Problem Solving, Communication and Collaboration. Communication Skill is one of the essential skills that should be mastered by the students. To master Communication Skills, students must first master their Language Skills. Language Skills is one of the main supporting factors in improving Communication Skills of a person because by learning Language Skills students are considered capable of communicating well and correctly so that the message or how to deliver the message to the listener can be conveyed clearly and easily understood. However, it cannot be denied that English output or learning outcomes which are less optimal is the problem which is frequently found in the implementation of the learning process. This research aimed to improve students’ language skills by developing learning model in English subject for VIII graders of SMP N 1 Uram Jaya through Directed-Project Based Learning (DPjBL) implementation. This study is designed in Research and Development (R & D) using ADDIE model development. The researcher collected data through observation, questionnaire, interview, test, and documentation which were then analyzed qualitatively and quantitatively. The results showed that DPjBL is effective to use, it is seen from the difference in value between the pretest and posttest of the control class and the experimental class. From the results of a questionnaire filled in general, the students and teachers agreed to DPjBL learning model. This learning model can increase the students' English achievement.

Keywords: language skills, learning model, Directed-Project Based Learning (DPjBL), English achievement

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16176 Gas Pressure Evaluation through Radial Velocity Measurement of Fluid Flow Modeled by Drift Flux Model

Authors: Aicha Rima Cheniti, Hatem Besbes, Joseph Haggege, Christophe Sintes

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In this paper, we consider a drift flux mixture model of the blood flow. The mixture consists of gas phase which is carbon dioxide and liquid phase which is an aqueous carbon dioxide solution. This model was used to determine the distributions of the mixture velocity, the mixture pressure, and the carbon dioxide pressure. These theoretical data are used to determine a measurement method of mean gas pressure through the determination of radial velocity distribution. This method can be applicable in experimental domain.

Keywords: mean carbon dioxide pressure, mean mixture pressure, mixture velocity, radial velocity

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16175 A Predictive Model of Supply and Demand in the State of Jalisco, Mexico

Authors: M. Gil, R. Montalvo

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Business Intelligence (BI) has become a major source of competitive advantages for firms around the world. BI has been defined as the process of data visualization and reporting for understanding what happened and what is happening. Moreover, BI has been studied for its predictive capabilities in the context of trade and financial transactions. The current literature has identified that BI permits managers to identify market trends, understand customer relations, and predict demand for their products and services. This last capability of BI has been of special concern to academics. Specifically, due to its power to build predictive models adaptable to specific time horizons and geographical regions. However, the current literature of BI focuses on predicting specific markets and industries because the impact of such predictive models was relevant to specific industries or organizations. Currently, the existing literature has not developed a predictive model of BI that takes into consideration the whole economy of a geographical area. This paper seeks to create a predictive model of BI that would show the bigger picture of a geographical area. This paper uses a data set from the Secretary of Economic Development of the state of Jalisco, Mexico. Such data set includes data from all the commercial transactions that occurred in the state in the last years. By analyzing such data set, it will be possible to generate a BI model that predicts supply and demand from specific industries around the state of Jalisco. This research has at least three contributions. Firstly, a methodological contribution to the BI literature by generating the predictive supply and demand model. Secondly, a theoretical contribution to BI current understanding. The model presented in this paper incorporates the whole picture of the economic field instead of focusing on a specific industry. Lastly, a practical contribution might be relevant to local governments that seek to improve their economic performance by implementing BI in their policy planning.

Keywords: business intelligence, predictive model, supply and demand, Mexico

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16174 Advanced Bio-Composite Materials Based on Biopolymer Blends and Cellulose Nanocrystals

Authors: Zineb Kassab, Nassima El Miri, A. Aboulkas, Abdellatif Barakat, Mounir El Achaby

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Recently, more attention has been given to biopolymers with a focus on sustainable development and environmental preservation. Following this tendency, the attempt has been made to replace polymers derived from petroleum with superior biodegradable polymers (biopolymers). In this context, biopolymers are considered potential replacements for conventional plastic materials. However, some of their properties must be improved for better competitiveness, especially regarding their mechanical, thermal and barrier properties. Bio-nanocomposite technology using nanofillers has already been proven as an effective way to produce new materials with specific properties and high performances. With the emergence of nanostructured bio-composite materials, incorporating elongated rod-like cellulose nanocrystals (CNC) has attracted more and more attention in the field of nanotechnology. This study is aimed to develop bio-composite films of biopolymer matrices [Carboxymethyle cellulose (CMC), Starch (ST), Chitosan (CS) and Polyvinyl alcohol (PVA)] reinforced with cellulose nanocrystals (CNC) using the solution casting method. The CNC were extracted at a nanometric scale from lignocellulosic fibers via sulfuric acid hydrolysis and then characterized using X-ray diffraction (XRD), thermogravimetric analysis (TGA), confocal microscopy, infrared spectroscopy (IR), atomic force and transmission electron microscopies (AFM and TEM) techniques. The as extracted CNC were used as a reinforcing phase to produce a variety of bio-composite films at different CNC loading (0.5-10 wt %) with specific properties. The rheological properties of film-forming solutions (FFS) of bio-composites were studied, and their relation to the casting process was evaluated. Then, the structural, optical transparency, water vapor permeability, thermal stability and mechanical properties of all prepared bio-composite films were evaluated and studied in this report. The high performances of these bio-composite films are expected to have potential in biomaterials or packaging applications.

Keywords: biopolymer composites, cellulose nanocrystals, food packaging, lignocellulosic fibers

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16173 Market Integration in the ECCAS Sub-Region

Authors: Mouhamed Mbouandi Njikam

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This work assesses the trade potential of countries in the Economic Community of Central Africa States (ECCAS). The gravity model of trade is used to evaluate the trade flows of member countries, and to compute the trade potential index of ECCAS during 1995-2010. The focus is on the removal of tariffs and non-tariff barriers in the sub-region. Estimates from the gravity model are used for the calculation of the sub-region’s commercial potential. Its three main findings are: (i) the background research shows a low level of integration in the sub-region and open economies; (ii) a low level of industrialization and diversification are the main factors reducing trade potential in the sub-region; (iii) the trade creation predominate on the deflections of trade between member countries.

Keywords: gravity model, ECCAS, trade flows, trade potential, regional cooperation

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16172 Development of Time Series Forecasting Model for Dengue Cases in Nakhon Si Thammarat, Southern Thailand

Authors: Manit Pollar

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Identifying the dengue epidemic periods early would be helpful to take necessary actions to prevent the dengue outbreaks. Providing an accurate prediction on dengue epidemic seasons will allow sufficient time to take the necessary decisions and actions to safeguard the situation for local authorities. This study aimed to develop a forecasting model on number of dengue incidences in Nakhon Si Thammarat Province, Southern Thailand using time series analysis. We develop Seasonal Autoregressive Moving Average (SARIMA) models on the monthly data collected between 2003-2011 and validated the models using data collected between January-September 2012. The result of this study revealed that the SARIMA(1,1,0)(1,2,1)12 model closely described the trends and seasons of dengue incidence and confirmed the existence of dengue fever cases in Nakhon Si Thammarat for the years between 2003-2011. The study showed that the one-step approach for predicting dengue incidences provided significantly more accurate predictions than the twelve-step approach. The model, even if based purely on statistical data analysis, can provide a useful basis for allocation of resources for disease prevention.

Keywords: SARIMA, time series model, dengue cases, Thailand

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16171 Structural Analysis and Detail Design of APV Module Structure Using Topology Optimization Design

Authors: Hyun Kyu Cho, Jun Soo Kim, Young Hoon Lee, Sang Hoon Kang, Young Chul Park

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In the study, structure for one of offshore drilling system APV(Air Pressure Vessle) modules was designed by using topology optimum design and performed structural safety evaluation according to DNV rules. 3D model created base on design area and non-design area separated by using topology optimization for the environmental loads. This model separated 17 types for wind loads and dynamic loads and performed structural analysis evaluation for each model. As a result, the maximum stress occurred 181.25MPa.

Keywords: APV, topology optimum design, DNV, structural analysis, stress

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16170 Developing Integrated Model for Building Design and Evacuation Planning

Authors: Hao-Hsi Tseng, Hsin-Yun Lee

Abstract:

In the process of building design, the designers have to complete the spatial design and consider the evacuation performance at the same time. It is usually difficult to combine the two planning processes and it results in the gap between spatial design and evacuation performance. Then the designers cannot complete an integrated optimal design solution. In addition, the evacuation routing models proposed by previous researchers is different from the practical evacuation decisions in the real field. On the other hand, more and more building design projects are executed by Building Information Modeling (BIM) in which the design content is formed by the object-oriented framework. Thus, the integration of BIM and evacuation simulation can make a significant contribution for designers. Therefore, this research plan will establish a model that integrates spatial design and evacuation planning. The proposed model will provide the support for the spatial design modifications and optimize the evacuation planning. The designers can complete the integrated design solution in BIM. Besides, this research plan improves the evacuation routing method to make the simulation results more practical. The proposed model will be applied in a building design project for evaluation and validation when it will provide the near-optimal design suggestion. By applying the proposed model, the integration and efficiency of the design process are improved and the evacuation plan is more useful. The quality of building spatial design will be better.

Keywords: building information modeling, evacuation, design, floor plan

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16169 Reduction of Cooling Demands in a Subtropical Humid Climate Zone: A Study on Roofs of Existing Residential Building Using Passive

Authors: Megha Jain, K. K. Pathak

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In sub-tropical humid climates, it is estimated most of the urban peak load of energy consumption is used to satisfy air-conditioning or air-coolers cooling demand in summer time. As the urbanization rate in developing nation – like the case in India is rising rapidly, the pressure placed on energy resources to satisfy inhabitants’ indoor comfort requirements is consequently increasing too. This paper introduces passive cooling through roof as a means of reducing energy cooling loads for satisfying human comfort requirements in a sub-tropical climate. Experiments were performed by applying different insulators which are locally available solar reflective materials to insulate the roofs of five rooms of 4 case buildings; three rooms having RCC (Reinforced Cement Concrete) roof and two having Asbestos sheet roof of existing buildings. The results are verified by computer simulation using Computational Fluid Dynamics tools with FLUENT software. The result of using solar reflective paint with high albedo coating shows a fall of 4.8⁰C in peak hours and saves 303 kWh considering energy load with air conditioner during the summer season in comparison to non insulated flat roof energy load of residential buildings in Bhopal. An optimum solution of insulator for both types of roofs is presented. It is recommended that the selected cool roof solution be combined with insulation on other elements of envelope, to increase the indoor thermal comfort. The application is intended for low cost residential buildings in composite and warm climate like Bhopal.

Keywords: cool roof, computational fluid dynamics, energy loads, insulators, passive cooling, subtropical climate, thermal performance

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16168 An Optimization Model for Waste Management in Demolition Works

Authors: Eva Queheille, Franck Taillandier, Nadia Saiyouri

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Waste management has become a major issue in demolition works, because of its environmental impact (energy consumption, resource consumption, pollution…). However, improving waste management requires to take also into account the overall demolition process and to consider demolition main objectives (e.g. cost, delay). Establishing a strategy with these conflicting objectives (economic and environment) remains complex. In order to provide a decision-support for demolition companies, a multi-objective optimization model was developed. In this model, a demolition strategy is computed from a set of 80 decision variables (worker team composition, machines, treatment for each type of waste, choice of treatment platform…), which impacts the demolition objectives. The model has experimented on a real-case study (demolition of several buildings in France). To process the optimization, different optimization algorithms (NSGA2, MOPSO, DBEA…) were tested. Results allow the engineer in charge of this case, to build a sustainable demolition strategy without affecting cost or delay.

Keywords: deconstruction, life cycle assessment, multi-objective optimization, waste management

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16167 Towards an Effective Approach for Modelling near Surface Air Temperature Combining Weather and Satellite Data

Authors: Nicola Colaninno, Eugenio Morello

Abstract:

The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

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16166 Application of Public Access Two-Dimensional Hydrodynamic and Distributed Hydrological Models for Flood Forecasting in Ungauged Basins

Authors: Ahmad Shayeq Azizi, Yuji Toda

Abstract:

In Afghanistan, floods are the most frequent and recurrent events among other natural disasters. On the other hand, lack of monitoring data is a severe problem, which increases the difficulty of making the appropriate flood countermeasures of flood forecasting. This study is carried out to simulate the flood inundation in Harirud River Basin by application of distributed hydrological model, Integrated Flood Analysis System (IFAS) and 2D hydrodynamic model, International River Interface Cooperative (iRIC) based on satellite rainfall combined with historical peak discharge and global accessed data. The results of the simulation can predict the inundation area, depth and velocity, and the hardware countermeasures such as the impact of levee installation can be discussed by using the present method. The methodology proposed in this study is suitable for the area where hydrological and geographical data including river survey data are poorly observed.

Keywords: distributed hydrological model, flood inundation, hydrodynamic model, ungauged basins

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16165 Numerical Modeling of Flow in USBR II Stilling Basin with End Adverse Slope

Authors: Hamidreza Babaali, Alireza Mojtahedi, Nasim Soori, Saba Soori

Abstract:

Hydraulic jump is one of the effective ways of energy dissipation in stilling basins that the ‎energy is highly dissipated by jumping. Adverse slope surface at the end stilling basin is ‎caused to increase energy dissipation and stability of the hydraulic jump. In this study, the adverse slope ‎has been added to end of United States Bureau of Reclamation (USBR) II stilling basin in hydraulic model of Nazloochay dam with scale 1:40, and flow simulated into stilling basin using Flow-3D ‎software. The numerical model is verified by experimental data of water depth in ‎stilling basin. Then, the parameters of water level profile, Froude Number, pressure, air ‎entrainment and turbulent dissipation investigated for discharging 300 m3/s using K-Ɛ and Re-Normalization Group (RNG) turbulence ‎models. The results showed a good agreement between numerical and experimental model‎ as ‎numerical model can be used to optimize of stilling basins.‎

Keywords: experimental and numerical modelling, end adverse slope, flow ‎parameters, USBR II stilling basin

Procedia PDF Downloads 173
16164 A Novel Machining Method and Tool-Path Generation for Bent Mandrel

Authors: Hong Lu, Yongquan Zhang, Wei Fan, Xiangang Su

Abstract:

Bent mandrel has been widely used as precise mould in automobile industry, shipping industry and aviation industry. To improve the versatility and efficiency of turning method of bent mandrel with fixed rotational center, an instantaneous machining model based on cutting parameters and machine dimension is prospered in this paper. The spiral-like tool path generation approach in non-axisymmetric turning process of bent mandrel is developed as well to deal with the error of part-to-part repeatability in existed turning model. The actual cutter-location points are calculated by cutter-contact points, which are obtained from the approach of spiral sweep process using equal-arc-length segment principle in polar coordinate system. The tool offset is set to avoid the interference between tool and work piece is also considered in the machining model. Depend on the spindle rotational angle, synchronization control of X-axis, Z-axis and C-axis is adopted to generate the tool-path of the turning process. The simulation method is developed to generate NC program according to the presented model, which includes calculation of cutter-location points and generation of tool-path of cutting process. With the approach of a bent mandrel taken as an example, the maximum offset of center axis is 4mm in the 3D space. Experiment results verify that the machining model and turning method are appropriate for the characteristics of bent mandrel.

Keywords: bent mandrel, instantaneous machining model, simulation method, tool-path generation

Procedia PDF Downloads 331
16163 Assessing Effects of an Intervention on Bottle-Weaning and Reducing Daily Milk Intake from Bottles in Toddlers Using Two-Part Random Effects Models

Authors: Yungtai Lo

Abstract:

Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

Procedia PDF Downloads 344
16162 Building Exoskeletons for Seismic Retrofitting

Authors: Giuliana Scuderi, Patrick Teuffel

Abstract:

The proven vulnerability of the existing social housing building heritage to natural or induced earthquakes requires the development of new design concepts and conceptual method to preserve materials and object, at the same time providing new performances. An integrate intervention between civil engineering, building physics and architecture can convert the social housing districts from a critical part of the city to a strategic resource of revitalization. Referring to bio-mimicry principles the present research proposes a taxonomy with the exoskeleton of the insect, an external, light and resistant armour whose role is to protect the internal organs from external potentially dangerous inputs. In the same way, a “building exoskeleton”, acting from the outside of the building as an enclosing cage, can restore, protect and support the existing building, assuming a complex set of roles, from the structural to the thermal, from the aesthetical to the functional. This study evaluates the structural efficiency of shape memory alloys devices (SMADs) connecting the “building exoskeleton” with the existing structure to rehabilitate, in order to prevent the out-of-plane collapse of walls and for the passive dissipation of the seismic energy, with a calibrated operability in relation to the intensity of the horizontal loads. The two case studies of a masonry structure and of a masonry structure with concrete frame are considered, and for each case, a theoretical social housing building is exposed to earthquake forces, to evaluate its structural response with or without SMADs. The two typologies are modelled with the finite element program SAP2000, and they are respectively defined through a “frame model” and a “diagonal strut model”. In the same software two types of SMADs, called the 00-10 SMAD and the 05-10 SMAD are defined, and non-linear static and dynamic analyses, namely push over analysis and time history analysis, are performed to evaluate the seismic response of the building. The effectiveness of the devices in limiting the control joint displacements resulted higher in one direction, leading to the consideration of a possible calibrated use of the devices in the different walls of the building. The results show also a higher efficiency of the 00-10 SMADs in controlling the interstory drift, but at the same time the necessity to improve the hysteretic behaviour, to maximise the passive dissipation of the seismic energy.

Keywords: adaptive structure, biomimetic design, building exoskeleton, social housing, structural envelope, structural retrofitting

Procedia PDF Downloads 416