Search results for: material constitutive models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4315

Search results for: material constitutive models

3745 Synthetic Daily Flow Duration Curves for the Çoruh River Basin, Turkey

Authors: Fatih Tosunoğlu, İbrahim Can

Abstract:

The flow duration curve (FDC) is an informative method that represents the flow regime’s properties for a river basin. Therefore, the FDC is widely used for water resource projects such as hydropower, water supply, irrigation and water quality management. The primary purpose of this study is to obtain synthetic daily flow duration curves for Çoruh Basin, Turkey. For this aim, we firstly developed univariate auto-regressive moving average (ARMA) models for daily flows of 9 stations located in Çoruh basin and then these models were used to generate 100 synthetic flow series each having same size as historical series. Secondly, flow duration curves of each synthetic series were drawn and the flow values exceeded 10, 50 and 95% of the time and 95% confidence limit of these flows were calculated. As a result, flood, mean and low flows potential of Çoruh basin will comprehensively be represented.

Keywords: ARMA models, Çoruh basin, flow duration curve, Turkey.

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3744 Mesoporous Material Nanofibers by Electrospinning

Authors: Sh. Sohrabnezhad, A. Jafarzadeh

Abstract:

In this paper, MCM-41 mesoporous material nanofibers were synthesized by an electrospinning technique. The nanofibers were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), x-ray diffraction (XRD), and nitrogen adsorption–desorption measurement. Tetraethyl orthosilicate (TEOS) and polyvinyl alcohol (PVA) were used as a silica source and fiber forming source, respectively. TEM and SEM images showed synthesis of MCM-41 nanofibers with a diameter of 200 nm. The pore diameter and surface area of calcined MCM-41 nanofibers was 2.2 nm and 970 m2/g, respectively. The morphology of the MCM-41 nanofibers depended on spinning voltages.

Keywords: Electrospinning, electron microscopy, fiber technology, porous materials, X-ray techniques.

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3743 A Quantitative Approach to Strategic Design of Component-Based Business Process Models

Authors: Eakong Atiptamvaree, Twittie Senivongse

Abstract:

A new paradigm for software design and development models software by its business process, translates the model into a process execution language, and has it run by a supporting execution engine. This process-oriented paradigm promotes modeling of software by less technical users or business analysts as well as rapid development. Since business process models may be shared by different organizations and sometimes even by different business domains, it is interesting to apply a technique used in traditional software component technology to design reusable business processes. This paper discusses an approach to apply a technique for software component fabrication to the design of process-oriented software units, called process components. These process components result from decomposing a business process of a particular application domain into subprocesses with an aim that the process components can be reusable in different process-based software models. The approach is quantitative because the quality of process component design is measured from technical features of the process components. The approach is also strategic because the measured quality is determined against business-oriented component management goals. A software tool has been developed to measure how good a process component design is, according to the required managerial goals and comparing to other designs. We also discuss how we benefit from reusable process components.

Keywords: Business process model, process component, component management goals, measurement

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3742 A Comparative Study on ANN, ANFIS and SVM Methods for Computing Resonant Frequency of A-Shaped Compact Microstrip Antennas

Authors: Ahmet Kayabasi, Ali Akdagli

Abstract:

In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: A-shaped compact microstrip antenna, Artificial Neural Network (ANN), adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM).

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3741 Wheat Yield Prediction through Agro Meteorological Indices for Ardebil District

Authors: Fariba Esfandiary, Ghafoor Aghaie, Ali Dolati Mehr

Abstract:

Wheat prediction was carried out using different meteorological variables together with agro meteorological indices in Ardebil district for the years 2004-2005 & 2005–2006. On the basis of correlation coefficients, standard error of estimate as well as relative deviation of predicted yield from actual yield using different statistical models, the best subset of agro meteorological indices were selected including daily minimum temperature (Tmin), accumulated difference of maximum & minimum temperatures (TD), growing degree days (GDD), accumulated water vapor pressure deficit (VPD), sunshine hours (SH) & potential evapotranspiration (PET). Yield prediction was done two months in advance before harvesting time which was coincide with commencement of reproductive stage of wheat (5th of June). It revealed that in the final statistical models, 83% of wheat yield variability was accounted for variation in above agro meteorological indices.

Keywords: Wheat yields prediction, agro meteorological indices, statistical models

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3740 The Effect of Interlamellar Distance in Pearlite on CGI Machining

Authors: Anders Berglund, Cornel Mihai Nicolescu, Henrik Svensson

Abstract:

Swedish truck industry is investigating the possibility for implementing the use of Compacted Graphite Iron (CGI) in their heavy duty diesel engines. Compared to the alloyed gray iron used today, CGI has superior mechanical properties but not as good machinability. Another issue that needs to be addressed when implementing CGI is the inhomogeneous microstructure when the cast component has different section thicknesses, as in cylinder blocks. Thinner sections results in finer pearlite, in the material, with higher strength. Therefore an investigation on its influence on machinability was needed. This paper focuses on the effect that interlamellar distance in pearlite has on CGI machinability and material physical properties. The effect of pearlite content and nodularity is also examined. The results showed that interlamellar distance in pearlite did not have as large effect on the material physical properties or machinability as pearlite content. The paper also shows the difficulties of obtaining a homogeneous microstructure in inhomogeneous workpieces.

Keywords: Compacted graphite iron (CGI), machinability, microstructure, milling, interlamellar distance in pearlite.

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3739 Determination of Material Properties for Biodegradable Polylactic Acid Plastic Used in 3D Printers

Authors: Juraj Beniak, Ľubomír Šooš, Peter Križan, Miloš Matúš

Abstract:

Within Rapid Prototyping technologies are used many types of materials. Many of them are recyclable but there are still as plastic like, so practically they do not degrade in the landfill. Polylactic acid (PLA) is one of the special plastic materials, which are biodegradable and available for 3D printing within Fused Deposition Modeling (FDM) technology. The question is, if the mechanical properties of produced models are comparable to similar technical plastic materials which are usual for prototype production. Presented paper shows the experiments results for tensile strength measurements for specimens prepared with different 3D printer settings and model orientation. Paper contains also the comparison of tensile strength values with values measured on specimens produced by conventional technologies as injection moulding.

Keywords: 3D printing, biodegradable plastic, fused deposition modeling, PLA plastic, rapid prototyping.

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3738 Fuzzy Estimation of Parameters in Statistical Models

Authors: A. Falsafain, S. M. Taheri, M. Mashinchi

Abstract:

Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameters of two Normal distributions, as well as the parameters of the Exponential and Poisson distributions.

Keywords: Confidence interval. Fuzzy number. Fuzzy estimation.

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3737 Identification of the Best Blend Composition of Natural Rubber-High Density Polyethylene Blends for Roofing Applications

Authors: W. V. W. H. Wickramaarachchi, S. Walpalage, S. M. Egodage

Abstract:

Thermoplastic elastomer (TPE) is a multifunctional polymeric material which possesses a combination of excellent properties of parent materials. Basically, TPE has a rubber phase and a thermoplastic phase which gives processability as thermoplastics. When the rubber phase is partially or fully crosslinked in the thermoplastic matrix, TPE is called as thermoplastic elastomer vulcanizate (TPV). If the rubber phase is non-crosslinked, it is called as thermoplastic elastomer olefin (TPO). Nowadays TPEs are introduced into the commercial market with different products. However, the application of TPE as a roofing material is limited. Out of the commercially available roofing products from different materials, only single ply roofing membranes and plastic roofing sheets are produced from rubbers and plastics. Natural rubber (NR) and high density polyethylene (HDPE) are used in various industrial applications individually with some drawbacks. Therefore, this study was focused to develop both TPO and TPV blends from NR and HDPE at different compositions and then to identify the best blend composition to use as a roofing material. A series of blends by varying NR loading from 10 wt% to 50 wt%, at 10 wt% intervals, were prepared using a twin screw extruder. Dicumyl peroxide was used as a crosslinker for TPV. The standard properties for a roofing material like tensile properties tear strength, hardness, impact strength, water absorption, swell/gel analysis and thermal characteristics of the blends were investigated. Change of tensile strength after exposing to UV radiation was also studied. Tensile strength, hardness, tear strength, melting temperature and gel content of TPVs show higher values compared to TPOs at every loading studied, while water absorption and swelling index show lower values, suggesting TPVs are more suitable than TPOs for roofing applications. Most of the optimum properties were shown at 10/90 (NR/HDPE) composition. However, high impact strength and gel content were shown at 20/80 (NR/HDPE) composition. Impact strength, as being an energy absorbing property, is the most important for a roofing material in order to resist impact loads. Therefore, 20/80 (NR/HDPE) is identified as the best blend composition. UV resistance and other properties required for a roofing material could be achieved by incorporating suitable additives to TPVs.

Keywords: Thermoplastic elastomer, natural rubber, high density polyethylene, roofing material.

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3736 Artificial Intelligence-Based Detection of Individuals Suffering from Vestibular Disorder

Authors: D. Hişam, S. İkizoğlu

Abstract:

Identifying the problem behind balance disorder is one of the most interesting topics in medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three ML models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest (RF) Classifier was the most accurate model.

Keywords: Vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting.

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3735 Acoustic and Thermal Insulating Materials Based On Natural Fibres Used in Floor Construction

Authors: J. Hroudova, J. Zach

Abstract:

The majority of contemporary insulation materials commonly used in the building industry is made from non-renewable raw materials; furthermore, their production often brings high energy costs. A long-term trend as far as sustainable development is concerned has been the reduction of energy and material demands of building material production. One of the solutions is the possibility of using easily renewable natural raw material sources which are considerably more ecological and their production is mostly less energy-consuming compared to the production of normal insulations (mineral wool, polystyrene). The paper describes the results of research focused on the development of thermal and acoustic insulation materials based on natural fibres intended for floor constructions. Given the characteristic open porosity of natural fibre materials, the hygrothermal behaviour of the developed materials was studied. Especially the influence of relative humidity and temperature on thermal insulation properties was observed.

Keywords: Green thermal and acoustic insulating materials, natural fibres, technical hemp, flax, floor construction.

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3734 Statistical Analysis and Impact Forecasting of Connected and Autonomous Vehicles on the Environment: Case Study in the State of Maryland

Authors: Alireza Ansariyar, Safieh Laaly

Abstract:

Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates Connected and Autonomous Vehicles (CAVs) fuel consumption and air pollutants including Carbon Monoxide (CO), Particulate Matter (PM), and Nitrogen Oxides (NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: Connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models.

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3733 Cd2+ Ions Removal from Aqueous Solutions Using Alginite

Authors: Vladimír Frišták, Martin Pipíška, Juraj Lesný

Abstract:

Alginite has been evaluated as an efficient pollution control material. In this paper, alginite from maar Pinciná (SR) for removal of Cd2+ ions from aqueous solution was studied. The potential sorbent was characterized by X-ray fluorescence analysis (RFA) analysis, Fourier transform infrared spectral analysis (FT-IR) and specific surface area (SSA) was also determined. The sorption process was optimized from the point of initial cadmium concentration effect and effect of pH value. The Freundlich and Langmuir models were used to interpret the sorption behavior of Cd2+ ions, and the results showed that experimental data were well fitted by the Langmuir equation. Alginite maximal sorption capacity (Qmax) for Cd2+ ions calculated from Langmuir isotherm was 34 mg/g. Sorption process was significantly affected by initial pH value in the range from 4.0-7.0. Alginite is a comparable sorbent with other materials for toxic metals removal. 

Keywords: Alginites, Cd2+, sorption, Qmax

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3732 Predicting Depth of Penetration in Abrasive Waterjet Cutting of Polycrystalline Ceramics

Authors: S. Srinivas, N. Ramesh Babu

Abstract:

This paper presents a model to predict the depth of penetration in polycrystalline ceramic material cut by abrasive waterjet. The proposed model considered the interaction of cylindrical jet with target material in upper region and neglected the role of threshold velocity in lower region. The results predicted with the proposed model are validated with the experimental results obtained with Silicon Carbide (SiC) blocks.

Keywords: Abrasive waterjet cutting, analytical modeling, ceramics, microcutting and intergranular cracking.

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3731 Lean Impact Analysis Assessment Models: Development of a Lean Measurement Structural Model

Authors: Catherine Maware, Olufemi Adetunji

Abstract:

The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: Impact measurement model, lean bundles, lean manufacturing, organizational performance.

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3730 Breast Cancer Prediction Using Score-Level Fusion of Machine Learning and Deep Learning Models

Authors: [email protected]

Abstract:

Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data need a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM), ensemble learning with hyper parameters optimization, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: Machine learning, Deep learning, cancer prediction, breast cancer, LSTM, Score-Level Fusion.

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3729 Investigation of Drying Kinetics of Viscose Yarn Bobbins

Authors: Ugur Akyol, Dinçer Akal, Ahmet Cihan, Kamil Kahveci

Abstract:

This study is concerned with the investigation of the suitability of several empirical and semi-empirical drying models available in the literature to define drying behavior of viscose yarn bobbins. For this purpose, firstly, experimental drying behaviour of viscose bobbins was determined on an experimental dryer setup which was designed and manufactured based on hot-air bobbin dryers used in textile industry. Afterwards, drying models considered were fitted to the experimentally obtained moisture ratios. Drying parameters were drying temperature and bobbin diameter. The fit was performed by selecting the values for constants in the models in such a way that these values make the sum of the squared differences between the experimental and the model results for moisture ratio minimum. Suitability of fitting was specified as comparing the correlation coefficient, standard error and mean square deviation. The results show that the most appropriate model in describing the drying curves of viscose bobbins is the Page model.

Keywords: Drying, moisture ratio, Page model, viscose

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3728 Parameters Optimization of the Laminated Composite Plate for Sound Transmission Problem

Authors: Yu T. Tsai, Jin H. Huang

Abstract:

In this paper, the specific sound Transmission Loss (TL) of the Laminated Composite Plate (LCP) with different material properties in each layer is investigated. The numerical method to obtain the TL of the LCP is proposed by using elastic plate theory. The transfer matrix approach is novelty presented for computational efficiency in solving the numerous layers of dynamic stiffness matrix (D-matrix) of the LCP. Besides the numerical simulations for calculating the TL of the LCP, the material properties inverse method is presented for the design of a laminated composite plate analogous to a metallic plate with a specified TL. As a result, it demonstrates that the proposed computational algorithm exhibits high efficiency with a small number of iterations for achieving the goal. This method can be effectively employed to design and develop tailor-made materials for various applications.

Keywords: Sound transmission loss, laminated composite plate, transfer matrix approach, inverse problem, elastic plate theory, material properties.

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3727 Multi-Layer Perceptron and Radial Basis Function Neural Network Models for Classification of Diabetic Retinopathy Disease Using Video-Oculography Signals

Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

Abstract:

Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: Diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography.

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3726 Variation of CONWIP Systems

Authors: Joshua Prakash, Chin Jeng Feng

Abstract:

The paper describes the workings for four models of CONWIP systems used till date; the basic CONWIP system, the hybrid CONWIP system, the multi-product CONWIP system, and the parallel CONWIP system. The final novel model is introduced in this paper in a general form. These models may be adopted for analysis for both simulation studies and implementation on the shop floor. For each model, input parameters of interest are highlighted and their impacts on several system performance measures are addressed.

Keywords: CONWIP, hybrid CONWIP, mixed CONWIP, multi-product CONWIP.

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3725 Spatial Time Series Models for Rice and Cassava Yields Based On Bayesian Linear Mixed Models

Authors: Panudet Saengseedam, Nanthachai Kantanantha

Abstract:

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, Linear mixed model, Multivariate conditional autoregressive model, Spatial time series.

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3724 Logistics Outsourcing: Performance Models and Financial and Operational Indicators

Authors: Carlos Sanchís-Pedregosa, José A. D. M achuca, María del Mar González-Zamora

Abstract:

The growing outsourcing of logistics services resulting from the ongoing current in firms of costs reduction/increased efficiency means that it is becoming more and more important for the companies doing the outsourcing to carry out a proper evaluation. The multiple definitions and measures of logistics service performance found in research on the topic create a certain degree of confusion and do not clear the way towards the proper measurement of their performance. Do a model and a specific set of indicators exist that can be considered appropriate for measuring the performance of logistics services outsourcing in industrial environments? Are said indicators in keeping with the objectives pursued by outsourcing? We aim to answer these and other research questions in the study we have initiated in the field within the framework of the international High Performance Manufacturing (HPM) project of which this paper forms part. As the first stage of this research, this paper reviews articles dealing with the topic published in the last 15 years with the aim of detecting the models most used to make this measurement and determining which performance indicators are proposed as part of said models and which are most used. The first steps are also taken in determining whether these indicators, financial and operational, cover the aims that are being pursued when outsourcing logistics services. The findings show there is a wide variety of both models and indicators used. This would seem to testify to the need to continue with our research in order to try to propose a model and a set of indicators for measuring the performance of logistics services outsourcing in industrial environments.

Keywords: Logistics, objectives, outsourcing, performancemeasurement systems

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3723 Vibration of a Beam on an Elastic Foundation Using the Variational Iteration Method

Authors: Desmond Adair, Kairat Ismailov, Martin Jaeger

Abstract:

Modelling of Timoshenko beams on elastic foundations has been widely used in the analysis of buildings, geotechnical problems, and, railway and aerospace structures. For the elastic foundation, the most widely used models are one-parameter mechanical models or two-parameter models to include continuity and cohesion of typical foundations, with the two-parameter usually considered the better of the two. Knowledge of free vibration characteristics of beams on an elastic foundation is considered necessary for optimal design solutions in many engineering applications, and in this work, the efficient and accurate variational iteration method is developed and used to calculate natural frequencies of a Timoshenko beam on a two-parameter foundation. The variational iteration method is a technique capable of dealing with some linear and non-linear problems in an easy and efficient way. The calculations are compared with those using a finite-element method and other analytical solutions, and it is shown that the results are accurate and are obtained efficiently. It is found that the effect of the presence of the two-parameter foundation is to increase the beam’s natural frequencies and this is thought to be because of the shear-layer stiffness, which has an effect on the elastic stiffness. By setting the two-parameter model’s stiffness parameter to zero, it is possible to obtain a one-parameter foundation model, and so, comparison between the two foundation models is also made.

Keywords: Timoshenko beam, variational iteration method, two-parameter elastic foundation model.

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3722 Reduce, Reuse and Recycle: Grand Challenges in Construction Recovery Process

Authors: Abioye A. Oyenuga, Rao Bhamidimarri

Abstract:

Hurling a successful Construction and Demolition Waste (C&DW) recycling operation around the globe is a challenge today, predominantly because secondary materials markets are yet to be integrated. Reducing, Reusing and recycling of (C&DW) have been employed over the years, and various techniques have been investigated. However, the economic and environmental viability of its application seems limited. This paper discusses the costs and benefits in using secondary materials and focus on investigating reuse and recycling process for five major types of construction materials: concrete, metal, wood, cardboard/paper and plasterboard. Data obtained from demolition specialists and contractors are considered and evaluated. The research paper found that construction material recovery process fully incorporate a 3R’s principle contributing to saving energy and natural resources. This scrutiny leads to the empathy of grand challenges in construction material recovery process. Recommendations to deepen material recovery process are also discussed.

Keywords: Construction & Demolition Waste (C&DW), 3R concept, Recycling, Reuse, Life-Cycle Assessment (LCA), Waste Management.

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3721 Influence of Single and Multiple Skin-Core Debonding on Free Vibration Characteristics of Innovative GFRP Sandwich Panels

Authors: Indunil Jayatilake, Warna Karunasena, Weena Lokuge

Abstract:

An Australian manufacturer has fabricated an innovative GFRP sandwich panel made from E-glass fiber skin and a modified phenolic core for structural applications. Debonding, which refers to separation of skin from the core material in composite sandwiches, is one of the most common types of damage in composites. The presence of debonding is of great concern because it not only severely affects the stiffness but also modifies the dynamic behaviour of the structure. Generally it is seen that the majority of research carried out has been concerned about the delamination of laminated structures whereas skin-core debonding has received relatively minor attention. Furthermore it is observed that research done on composite slabs having multiple skin-core debonding is very limited. To address this gap, a comprehensive research investigating dynamic behaviour of composite panels with single and multiple debonding is presented. The study uses finite-element modelling and analyses for investigating the influence of debonding on free vibration behaviour of single and multilayer composite sandwich panels. A broad parametric investigation has been carried out by varying debonding locations, debonding sizes and support conditions of the panels in view of both single and multiple debonding. Numerical models were developed with Strand7 finite element package by innovatively selecting the suitable elements to diligently represent their actual behavior. Three-dimensional finite element models were employed to simulate the physically real situation as close as possible, with the use of an experimentally and numerically validated finite element model. Comparative results and conclusions based on the analyses are presented. For similar extents and locations of debonding, the effect of debonding on natural frequencies appears greatly dependent on the end conditions of the panel, giving greater decrease in natural frequency when the panels are more restrained. Some modes are more sensitive to debonding and this sensitivity seems to be related to their vibration mode shapes. The fundamental mode seems generally the least sensitive mode to debonding with respect to the variation in free vibration characteristics. The results indicate the effectiveness of the developed three dimensional finite element models in assessing debonding damage in composite sandwich panels.

Keywords: Debonding, free vibration behaviour, GFRP sandwich panels, three dimensional finite element modelling.

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3720 VaR Forecasting in Times of Increased Volatility

Authors: Ivo Jánský, Milan Rippel

Abstract:

The paper evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices - DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model mean using the ARMA processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are estimated on the data from the in-sample period and their forecasting accuracy is evaluated on the out-of-sample data, which are more volatile. The main aim of the paper is to test whether a model estimated on data with lower volatility can be used in periods with higher volatility. The evaluation is based on the conditional coverage test and is performed on each stock index separately. The primary result of the paper is that the volatility is best modelled using a GARCH process and that an ARMA process pattern cannot be found in analyzed time series.

Keywords: VaR, risk analysis, conditional volatility, garch, egarch, tarch, moving average process, autoregressive process

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3719 Crash Severity Modeling in Urban Highways Using Backward Regression Method

Authors: F. Rezaie Moghaddam, T. Rezaie Moghaddam, M. Pasbani Khiavi, M. Ali Ghorbani

Abstract:

Identifying and classifying intersections according to severity is very important for implementation of safety related counter measures and effective models are needed to compare and assess the severity. Highway safety organizations have considered intersection safety among their priorities. In spite of significant advances in highways safety, the large numbers of crashes with high severities still occur in the highways. Investigation of influential factors on crashes enables engineers to carry out calculations in order to reduce crash severity. Previous studies lacked a model capable of simultaneous illustration of the influence of human factors, road, vehicle, weather conditions and traffic features including traffic volume and flow speed on the crash severity. Thus, this paper is aimed at developing the models to illustrate the simultaneous influence of these variables on the crash severity in urban highways. The models represented in this study have been developed using binary Logit Models. SPSS software has been used to calibrate the models. It must be mentioned that backward regression method in SPSS was used to identify the significant variables in the model. Consider to obtained results it can be concluded that the main factor in increasing of crash severity in urban highways are driver age, movement with reverse gear, technical defect of the vehicle, vehicle collision with motorcycle and bicycle, bridge, frontal impact collisions, frontal-lateral collisions and multi-vehicle crashes in urban highways which always increase the crash severity in urban highways.

Keywords: Backward regression, crash severity, speed, urbanhighways.

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3718 Topology Optimization of Aircraft Fuselage Structure

Authors: Muniyasamy Kalanchiam, Baskar Mannai

Abstract:

Topology Optimization is a defined as the method of determining optimal distribution of material for the assumed design space with functionality, loads and boundary conditions [1]. Topology optimization can be used to optimize shape for the purposes of weight reduction, minimizing material requirements or selecting cost effective materials [2]. Topology optimization has been implemented through the use of finite element methods for the analysis, and optimization techniques based on the method of moving asymptotes, genetic algorithms, optimality criteria method, level sets and topological derivatives. Case study of Typical “Fuselage design" is considered for this paper to explain the benefits of Topology Optimization in the design cycle. A cylindrical shell is assumed as the design space and aerospace standard pay loads were applied on the fuselage with wing attachments as constraints. Then topological optimization is done using Finite Element (FE) based software. This optimization results in the structural concept design which satisfies all the design constraints using minimum material.

Keywords: Fuselage, Topology optimization, payloads, designoptimization, Finite Element Analysis.

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3717 Reduction of Content of Lead and Zinc from Wastewater by Using of Metallurgical Waste

Authors: L. Rozumová, J. Seidlerová

Abstract:

The aim of this paper was to study the sorption properties of a blast furnace sludge used as the sorbent. The sorbent was utilized for reduction of content of lead and zinc ions. Sorbent utilized in this work was obtained from metallurgical industry from process of wet gas treatment in iron production. The blast furnace sludge was characterized by X-Ray diffraction, scanning electron microscopy, and XRFS spectroscopy. Sorption experiments were conducted in batch mode. The sorption of metal ions in the sludge was determined by correlation of adsorption isotherm models. The adsorption of lead and zinc ions was best fitted with Langmuir adsorption isotherms. The adsorption capacity of lead and zinc ions was 53.8 mg.g-1 and 10.7 mg.g-1, respectively. The results indicated that blast furnace sludge could be effectively used as secondary material and could be also employed as a low-cost alternative for the removal of heavy metals ions from wastewater.

Keywords: Blast furnace sludge, lead, zinc, sorption.

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3716 A Study of Two Disease Models: With and Without Incubation Period

Authors: H. C. Chinwenyi, H. D. Ibrahim, J. O. Adekunle

Abstract:

The incubation period is defined as the time from infection with a microorganism to development of symptoms. In this research, two disease models: one with incubation period and another without incubation period were studied. The study involves the use of a  mathematical model with a single incubation period. The test for the existence and stability of the disease free and the endemic equilibrium states for both models were carried out. The fourth order Runge-Kutta method was used to solve both models numerically. Finally, a computer program in MATLAB was developed to run the numerical experiments. From the results, we are able to show that the endemic equilibrium state of the model with incubation period is locally asymptotically stable whereas the endemic equilibrium state of the model without incubation period is unstable under certain conditions on the given model parameters. It was also established that the disease free equilibrium states of the model with and without incubation period are locally asymptotically stable. Furthermore, results from numerical experiments using empirical data obtained from Nigeria Centre for Disease Control (NCDC) showed that the overall population of the infected people for the model with incubation period is higher than that without incubation period. We also established from the results obtained that as the transmission rate from susceptible to infected population increases, the peak values of the infected population for the model with incubation period decrease and are always less than those for the model without incubation period.

Keywords: Asymptotic stability, incubation period, Routh-Hurwitz criterion, Runge Kutta method.

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