Search results for: material models

Authors: M. Imran Hossen Khan, M. Mahiuddin, M. A. Karim

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Drying is a food processing technique where simultaneous heat and mass transfer take place from surface to the center of the sample. Deformation of food materials during drying is a common physical phenomenon which affects the textural quality and taste of the dried product. Most of the plant-based food materials are porous and hygroscopic in nature that contains about 80-90% water in different cellular environments: intercellular environment and intracellular environment. Transport of this cellular water has a significant effect on material deformation during drying. However, understanding of the scale of deformation is very complex due to diverse nature and structural heterogeneity of food material. Knowledge about the effect of transport of cellular water on deformation of material during drying is crucial for increasing the energy efficiency and obtaining better quality dried foods. Therefore, the primary aim of this work is to investigate the effect of intracellular water transport on material deformation during drying. In this study, apple tissue was taken for the investigation. The experiment was carried out using 1H-NMR T2 relaxometry with a conventional dryer. The experimental results are consistent with the understanding that transport of intracellular water causes cellular shrinkage associated with the anisotropic deformation of whole apple tissue. Interestingly, it is found that the deformation of apple tissue takes place at different stages of drying rather than deforming at one time. Moreover, it is found that the penetration rate of heat energy together with the pressure gradient between intracellular and intercellular environments is the responsible force to rupture the cell membrane.

Keywords: heat and mass transfer, food material, intracellular water, cell rupture, deformation

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Authors: Rukiye Ertan

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In this study, a brake friction material composition was investigated experimentally related to the effects of the friction modifiers and abrasive proportions on the tribological properties. The investigation was based on a simple experimental formulation, consisting of seven friction materials with different proportions of abrasives (ZrSiO4 and Fe2O3) and friction modifiers (cashew dust). The friction materials were evaluated using a Chase friction tester. The tribological properties, such as the wear resistance and friction stability, depending on the test temperature and the number of braking were obtained related to the friction material ingredient proportions. The results showed that the tribological properties of the brake pad were greatly affected by the abrasive and then cashew dust proportion.

Keywords: brake pad, friction, wear, abrasives

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Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova

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We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.

Keywords: cybersecurity, epidemiology, cyber epidemiology, malware

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Authors: William Waddington, M. Jahir Rizvi

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Sail used to propel a vessel functions in a similar way to an aircraft wing. Traditionally, cloth and ropes were used to produce sails. However, there is one major problem with traditional sail design, the increase in turbulence and flow separation when compared to that of an aircraft wing with the same camber. This has led to the development of the solid wing sail focusing mainly on the sail shape. Traditional cloth sails are manufactured as a single element whereas solid wing sail is made of two segments. To the authors’ best knowledge, the phenomena behind the performances of this type of sail at various angles of wind direction with respect to a sailing vessel’s direction (known as the angle of attack) is still an area of mystery. Hence, in this study, the thrusts of a sailing vessel produced by wing sails constructed with various angles (22°, 24°, 26° and 28°) between the two segments have been compared to that of a traditional cloth sail made of carbon-fiber material. The reason for using carbon-fiber material is to achieve the correct and the exact shape of a commercially available mainsail. NACA 0024 and NACA 0016 foils have been used to generate two-segment wing sail shape which incorporates a flap between the first and the second segments. Both the two-dimensional and the three-dimensional sail models designed in commercial CAD software Solidworks have been analyzed through Computational Fluid Dynamics (CFD) techniques using Ansys CFX considering an apparent wind speed of 20.55 knots with an apparent wind angle of 31°. The results indicate that the thrust from traditional sail increases from 8.18 N to 8.26 N when the angle of attack is increased from 5° to 7°. However, the thrust value decreases if the angle of attack is further increased. A solid wing sail which possesses 20° angle between its two segments, produces thrusts from 7.61 N to 7.74 N with an increase in the angle of attack from 7° to 8°. The thrust remains steady up to 9° angle of attack and drops dramatically beyond 9°. The highest thrust values that can be obtained for the solid wing sails with 22°, 24°, 26° and 28° angle respectively between the two segments are 8.75 N, 9.10 N, 9.29 N and 9.19 N respectively. The optimum angle of attack for each of the solid wing sails is identified as 7° at which these thrust values are obtained. Therefore, it can be concluded that all the thrust values predicted for the solid wing sails of angles between the two segments above 20° are higher compared to the thrust predicted for the traditional sail. However, the best performance from a solid wing sail is expected when the sail is created with an angle between the two segments above 20° but below or equal to 26°. In addition, 1/29th scale models in the wind tunnel have been tested to observe the flow behaviors around the sails. The experimental results support the numerical observations as the flow behaviors are exactly the same.

Keywords: CFD, drag, sailing vessel, thrust, traditional sail, wing sail

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Authors: Opeyemi Elujulo, Aderonke Okoya, Kehinde Awokoya

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Molecularly imprinted polymers (MIP) for the adsorption of pyridine (PYD) was obtained from PYD (the template), styrene (the functional monomer), divinyl benzene (the crosslinker), benzoyl peroxide (the initiator), and water (the porogen). When the template was removed by solvent extraction, imprinted binding sites were left in the polymer material that are capable of selectively rebinding the target molecule. The material was characterized by Fourier transform infrared spectroscopy and differential scanning calorimetry. Batch adsorption experiments were performed to study the adsorption of the material in terms of adsorption kinetics, isotherms, and thermodynamic parameters. The results showed that the imprinted polymer exhibited higher affinity for PYD compared to non-imprinted polymer (NIP).

Keywords: molecularly imprinted polymer, bulk polymerization, environmental pollutant, adsorption

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Authors: Le Ngoc Hung, Abriak Nor Edine, Binetruy Christophe, Benzerzour Mahfoud, Shahrour Isam, Patrice Rivard

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Bottom ash from Municipal Solid Waste Incineration (MSWI) can be viewed as a typical granular material because these industrial by-products result from the incineration of various domestic wastes. MSWI bottom ashes are mainly used in road engineering in substitution of the traditional natural aggregates. As the characterization of their mechanical behavior is essential in order to use them, specific studies have been led over the past few years. In the first part of this paper, the mechanical behavior of MSWI bottom ash is studied with triaxial tests. After analysis of the experiment results, the simulation of triaxial tests is carried out by using the software package CESAR-LCPC. As the first approach in modeling of this new class material, the Mohr-Coulomb model was chosen to describe the evolution of material under the influence of external mechanical actions.

Keywords: bottom ash, granular material, triaxial test, mechanical behavior, simulation, Mohr-Coulomb model, CESAR-LCPC

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Authors: Pattra Pukdeekiat, Siriluk Ruangrungrote

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This work was originated to precisely determine direct solar radiation by using atmospheric physics models since the accurate prediction of solar radiation is necessary and useful for solar energy applications including atmospheric research. The possible models and techniques for a calculation of regional direct solar radiation were challenging and compulsory for the case of unavailable instrumental measurement. The investigation was mathematically governed by six astronomical parameters i.e. declination (δ), hour angle (ω), solar time, solar zenith angle (θz), extraterrestrial radiation (Iso) and eccentricity (E0) along with two atmospheric parameters i.e. air mass (mr) and dew point temperature at Bangna meteorological station (13.67° N, 100.61° E) in Bangkok, Thailand. Analyses of five models of solar radiation determination with the assumption of clear sky were applied accompanied by three statistical tests: Mean Bias Difference (MBD), Root Mean Square Difference (RMSD) and Coefficient of determination (R2) in order to validate the accuracy of obtainable results. The calculated direct solar radiation was in a range of 491-505 Watt/m2 with relative percentage error 8.41% for winter and 532-540 Watt/m2 with relative percentage error 4.89% for summer 2014. Additionally, dataset of seven continuous days, representing both seasons were considered with the MBD, RMSD and R2 of -0.08, 0.25, 0.86 and -0.14, 0.35, 3.29, respectively, which belong to Kumar model for winter and CSR model for summer. In summary, the determination of direct solar radiation based on atmospheric models and empirical equations could advantageously provide immediate and reliable values of the solar components for any site in the region without a constraint of actual measurement.

Keywords: atmospheric physics models, astronomical parameters, atmospheric parameters, clear sky condition

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Authors: Makram Ben Jeddou

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The ABC classification is widely used by managers for inventory control. The classical ABC classification is based on the Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to take into account other important criteria. From these models, we will consider the ZF model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score based on a normalized average between a good and a bad optimized index can affect the ABC items classification. We will then focus on the weights assigned to each index and propose a classification compromise.

Keywords: ABC classification, multi criteria inventory classification models, ZF-model

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

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Authors: Imene Skhakhfa, Lahbaci Ouerdachi

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To ensure the overall coherence of simulated results, it is necessary to develop a robust validation process. In many applications, it is no longer content to calibrate and validate the model only in relation to the hydro graph measured at the outlet, but we try to better simulate the functioning of the watershed in space. Therefore the timing also performs compared to other variables such as water level measurements in intermediate stations or groundwater levels. As part of this work, we limit ourselves to modeling flood of short duration for which the process of evapotranspiration is negligible. The main parameters to identify the models are related to the method of unit hydro graph (HU). Three different models were tested: SNYDER, CLARK and SCS. These models differ in their mathematical structure and parameters to be calibrated while hydrological data are the same, the initial water content and precipitation. The models are compared on the basis of their performance in terms six objective criteria, three global criteria and three criteria representing volume, peak flow, and the mean square error. The first type of criteria gives more weight to strong events whereas the second considers all events to be of equal weight. The results show that the calibrated parameter values are dependent and also highlight the problems associated with the simulation of low flow events and intermittent precipitation.

Keywords: model calibration, intensity, runoff, hydrograph

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Authors: Bernd Engel, Hassan Raheem Hassan

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Rotary draw bending is a method used for tube forming. During the tube bending process, the neutral axis moves towards the inner arc and the wall thickness changes in the cross section of the tube. Wall thinning of the tube takes place at the extrados, whereas wall thickening of the tube occurs at the intrados. This paper investigates the tube bending with rotary draw bending process using thick-walled tubes and different material properties (16Mo3 and 10CrMo9-10). The experimental tests and finite element simulations are used to calculate the variable characteristics (wall thickness distribution, neutral axis shifting and longitudinal strain distribution). These results are compared with results of a plasto-mechanical model. Moreover, the cross section distortion is investigated in this study. This study helped to get bends with smaller wall factor for different material properties.

Keywords: rotary draw bending, thick wall tube, material properties, material influence

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Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves

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The modeling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high-resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve denser and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high-resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.

Keywords: 3D models, environment, matching, pleiades

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Authors: Amina Bouhaouche, Zineb Kaoua, Lila Lahreche, Sid Ali Kaoua, Kamel Daoud

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The objective of this study is to present a novel approach for analyzing the solid dispersion and mixing performance by a numerical simulation method using solid works software of a monodisperse particles for a large span of time reached 20 minutes. To assure the viability of a numerical simulation, an experimental study of a binary mixture of monodiperse particles taken as free flowing material in a V blender was developed on the basis of relative standard deviation curves, and the arrangement of the particles in the vessel. The experimental results were discussed and compared to the numerical simulation results.

Keywords: non-cohesive material, solid mixing, solid works, v-blender

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Authors: Snehal L. Kadam, Shriniwas B. Kulkarni

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Flexible electrode material with high surface area and good electrochemical properties is the current trend captivating the researchers across globe for application in the next generation energy storage field. In the present work, crumpled sheet like reduced graphene oxide grown on carbon cloth by the hydrothermal method with a series of different deposition temperatures at fixed time. The influence of the deposition temperature on the structural, morphological, optical and supercapacitive properties of the electrode material was investigated by XRD, RAMAN, XPS, TEM, FE-SEM, UV-VISIBLE and electrochemical characterization techniques.The results show that the hydrothermally synthesized reduced graphene oxide on carbon cloth has sheet like mesoporous structure. The reduced graphene oxide material at 160°C exhibits the best supercapacitor performance, with a specific capacitance of 443 F/g at scan rate 5mV/sec. Moreover, stability studies show 97% capacitance retention over 1000 CV cycles. This result shows that hydrothermally synthesized RGO on carbon cloth is the potential electrode material and would be used in the next-generation wearable energy storage systems. The detailed analysis and results will be presented at the conference.

Keywords: graphene oxide, reduced graphene oxide, carbon cloth, deposition temperature, supercapacitor

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Authors: I. Ioannou, I. M. Gitman

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This study focused on the contribution of micro-mechanical parameters on the macro-mechanical response of short fiber composites, namely polypropylene matrix reinforced by glass fibers. In the framework of this paper, an attention has been given to the glass fibers length, as micromechanical parameter influences the overall macroscopic material’s behavior. Three dimensional numerical models were developed and analyzed through the concept of a Representative Volume Element (RVE). Results of the RVE-based approach were compared with analytical Halpin-Tsai’s model.

Keywords: effective properties, homogenization, representative volume element, short fiber reinforced composites

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Authors: Gonzalo García-Reyes

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Conformastat spherically symmetric exact solutions of Einstein's field equations representing matter distributions made of fluid both perfect and anisotropic from given solutions of Poisson's equation of Newtonian gravity are investigated. The approach is used in the construction of new relativistic models of thick spherical shells and three-component models of galaxies (bulge, disk, and dark matter halo), writing, in this case, the metric in cylindrical coordinates. In addition, the circular motion of test particles (rotation curves) along geodesics on the equatorial plane of matter configurations and the stability of the orbits against radial perturbations are studied. The models constructed satisfy all the energy conditions.

Keywords: general relativity, exact solutions, spherical symmetry, galaxy, kinematics and dynamics, dark matter

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Authors: Subhan Ahmad, Pradeep Bhargava, Ajay Chourasia

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Shear failure in reinforced concrete beams without shear reinforcement leads to loss of property and life since a very little or no warning occurs before failure as in case of flexural failure. Shear strength of reinforced concrete beams decreases as its depth increases. This phenomenon is generally called as the size effect. In this paper, a comparative analysis is performed to estimate the performance of shear strength models in capturing the size effect of reinforced concrete beams made with conventional concrete, self-compacting concrete, and recycled aggregate concrete. Four shear strength models that account for the size effect in shear are selected from the literature and applied on the datasets of slender reinforced concrete beams. Beams prepared with conventional concrete, self-compacting concrete, and recycled aggregate concrete are considered for the analysis. Results showed that all the four models captured the size effect in shear effectively and produced conservative estimates of the shear strength for beams made with normal strength conventional concrete. These models yielded unconservative estimates for high strength conventional concrete beams with larger effective depths ( > 450 mm). Model of Bazant and Kim (1984) captured the size effect precisely and produced conservative estimates of shear strength of self-compacting concrete beams at all the effective depths. Also, shear strength models considered in this study produced unconservative estimates of shear strength for recycled aggregate concrete beams at all effective depths.

Keywords: reinforced concrete beams; shear strength; prediction models; size effect

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Authors: Arezoo Rahmani, Rinez Thapa, Juha-Matti Aalto, Petri Turhanen, Jouko Vepsalainen, Vesa-PekkaLehto, Joakim Riikonen

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Production of Scandium (Sc) is a complicated process because Sc is found only in low concentrations in ores and the concentration of Sc is very low compared with other metals. Therefore, utilization of typical extraction processes such as solvent extraction is problematic in scandium extraction. The Adsorption/desorption method can be used, but it is challenging to prepare materials, which have good selectivity, high adsorption capacity, and high stability. Therefore, efficient and environmentally friendly methods for Sc extraction are needed. In this study, the nanoporous composite material was developed for extracting Sc from an Sc ore. The nanoporous composite material offers several advantageous properties such as large surface area, high chemical and mechanical stability, fast diffusion of the metals in the material and possibility to construct a filter out of the material with good flow-through properties. The nanoporous silicon material was produced by first stabilizing the surfaces with a silicon carbide layer and then functionalizing the surface with bisphosphonates that act as metal chelators. The surface area and porosity of the material were characterized by N₂ adsorption and the morphology was studied by scanning electron microscopy (SEM). The bisphosphonate content of the material was studied by thermogravimetric analysis (TGA). The concentration of metal ions in the adsorption/desorption experiments was measured with inductively coupled plasma mass spectrometry (ICP-MS). The maximum capacity of the material was 25 µmol/g Sc at pH=1 and 45 µmol/g Sc at pH=3, obtained from adsorption isotherm. The selectivity of the material towards Sc in artificial solutions containing several metal ions was studied at pH one and pH 3. The result shows good selectivity of the nanoporous composite towards adsorption of Sc. Scandium was less efficiently adsorbed from solution leached from the ore of Sc because of excessive amounts of iron (Fe), aluminum (Al) and titanium (Ti) which disturbed the adsorption process. For example, the concentration of Fe was more than 4500 ppm, while the concentration of Sc was only three ppm, approximately 1500 times lower. Precipitation methods were developed to lower the concentration of the metals other than Sc. Optimal pH for precipitation was found to be pH 4. The concentration of Fe, Al and Ti were decreased by 99, 70, 99.6%, respectively, while the concentration of Sc decreased only 22%. Despite the large reduction in the concentration of other metals, more work is needed to further increase the relative concentration of Sc compared with other metals to efficiently extract it using the developed nanoporous composite material. Nevertheless, the developed material may provide an affordable, efficient and environmentally friendly method to extract Sc on a large scale.

Keywords: adsorption, nanoporous silicon, ore solution, scandium

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Authors: Ravi Prasher

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In nanostructured material thermal transport is dominated by contact resistance. Theoretical models describing thermal transport at interfaces assume perfectly flat surface whereas in reality surfaces can be rough with roughness ranging from sub-nanoscale dimension to micron scale. Here we introduce a model which includes both nanoscale contact mechanics and nanoscale heat transfer for rough nanoscale surfaces. This comprehensive model accounts for the effect of phonon acoustic mismatch, mechanical properties, chemical properties and randomness of the rough surface.

Keywords: adhesion and contact resistance, Kaptiza resistance of rough surfaces, nanoscale thermal transport

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Authors: Anna Vanderbruggen, Kai Bachmann, Martin Rudolph, Rodrigo Serna

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Recycling of lithium-ion batteries has attracted a lot of attention in recent years and focuses primarily on valuable metals such as cobalt, nickel, and lithium. Despite the growth in graphite consumption and the fact that it is classified as a critical raw material in the European Union, USA, and Australia, there is little work focusing on graphite recycling. Thus, graphite is usually considered waste in recycling treatments, where graphite particles are concentrated in the “black mass”, a fine fraction below 1mm, which also contains the foils and the active cathode particles such as LiCoO2 or LiNiMnCoO2. To characterize the material, various analytical methods are applied, including X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), Atomic Absorption Spectrometry (AAS), and SEM-based automated mineralogy. The latter consists of the combination of a scanning electron microscopy (SEM) image analysis and energy-dispersive X-ray spectroscopy (EDS). It is a powerful and well-known method for primary material characterization; however, it has not yet been applied to secondary material such as black mass, which is a challenging material to analyze due to fine alloy particles and to the lack of an existing dedicated database. The aim of this research is to characterize the black mass depending on the metals recycling process in order to understand the liberation mechanisms of the active particles from the foils and their effect on the graphite particle surfaces and to understand their impact on the subsequent graphite flotation. Three industrial processes were taken into account: purely mechanical, pyrolysis-mechanical, and mechanical-hydrometallurgy. In summary, this article explores various and common challenges for graphite and secondary material characterization.

Keywords: automated mineralogy, characterization, graphite, lithium ion battery, recycling

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Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

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The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

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Authors: Thomas Arink, Isam Janajreh

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The petroleum industry generates significant amounts of waste in the form of drill cuttings, contaminated soil and oily sludge. Drill cuttings are a product of the off-shore drilling rigs, containing wet soil and total petroleum hydrocarbons (TPH). Contaminated soil comes from different on-shore sites and also contains TPH. The oily sludge is mainly residue or tank bottom sludge from storage tanks. The two main treatment methods currently used are incineration and thermal desorption (TD). Thermal desorption is a method where the waste material is heated to 450ºC in an anaerobic environment to release volatiles, the condensed volatiles can be used as a liquid fuel. For the thermal desorption unit dry contaminated soil is mixed with moist drill cuttings to generate a suitable mixture. By thermo gravimetric analysis (TGA) of the TD feedstock it was found that less than 50% of the TPH are released, the discharged material is stored in landfill. This study proposes co-gasification of petroleum waste with waste tires as an alternative to thermal desorption. Co-gasification with a high-calorific material is necessary since the petroleum waste consists of more than 60 wt% ash (soil/sand), causing its calorific value to be too low for gasification. Since the gasification process occurs at 900ºC and higher, close to 100% of the TPH can be released, according to the TGA. This work consists of three parts: 1. a mathematical gasification model, 2. a reactive flow CFD model and 3. experimental work on a drop tube reactor. Extensive material characterization was done by means of proximate analysis (TGA), ultimate analysis (CHNOS flash analysis) and calorific value measurements (Bomb calorimeter) for the input parameters of the mathematical and CFD model. The mathematical model is a zero dimensional model based on Gibbs energy minimization together with Lagrange multiplier; it is used to find the product species composition (molar fractions of CO, H2, CH4 etc.) for different tire/petroleum feedstock mixtures and equivalence ratios. The results of the mathematical model act as a reference for the CFD model of the drop-tube reactor. With the CFD model the efficiency and product species composition can be predicted for different mixtures and particle sizes. Finally both models are verified by experiments on a drop tube reactor (1540 mm long, 66 mm inner diameter, 1400 K maximum temperature).

Keywords: computational fluid dynamics (CFD), drop tube reactor, gasification, Gibbs energy minimization, petroleum waste, waste tires

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Authors: Awol Seid Ebrie

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HIV results as an incurable disease, AIDS. After a person is infected with virus, the virus gradually destroys all the infection fighting cells called CD4 cells and makes the individual susceptible to opportunistic infections which cause severe or fatal health problems. Several studies show that the CD4 cells count is the most determinant indicator of the effectiveness of the treatment or progression of the disease. The objective of this paper is to investigate the progression of the disease over time among patient under HAART treatment. Two main approaches of the generalized multilevel ordinal models; namely the proportional odds model and the nonproportional odds model have been applied to the HAART data. Also, the multilevel part of both models includes random intercepts and random coefficients. In general, four models are explored in the analysis and then the models are compared using the deviance information criteria. Of these models, the random coefficients nonproportional odds model is selected as the best model for the HAART data used as it has the smallest DIC value. The selected model shows that the progression of the disease increases as the time under the treatment increases. In addition, it reveals that gender, baseline clinical stage and functional status of the patient have a significant association with the progression of the disease.

Keywords: nonproportional odds model, proportional odds model, random coefficients model, random intercepts model

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Authors: M. Kagan Keler, Sibel Daglilar, Isil Kerti, Oguzhan Gunduz

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Electrospinning is a versatile way to occur fibers at nano-scale and polycaprolactone is a biomedical material which has a wide usage in cartilage defects and tissue regeneration. PCL is biocompatible and durable material which can be used in bio-implants. Therefore, electrospinning process was chosen as a fabrication method to get PCL fibers in an effective way because of its significant adjustments. In this research study, electrospinning parameters was evaluated during the producing of polymer tissue scaffolds. Polycaprolactone’s molecular weight was 80.000 Da and was employed as a tissue material in the electrospinning process. PCL was decomposed in dimethylformamid(DMF) and chloroform(CF) with the weight ratio of 1:1. Different compositions (1%, 3%, 5%, 10% and 20 %) of PCL was prepared in the laboratory conditions. All solvents with different percentages of PCL have been taken into the syringe and loaded into the electrospinning system. In electrospinning dozens of trial were applied to get homogeneously uniform scaffold samples. Taylor cone which is crucial point for electrospinning characteristic was occurred and changed in different voltages up to the material compositions’ conductivity. While the PCL percentages were increasing in the electrospinning, structure started to arise with droplets, which was an expressive problem for tissue scaffold. The vertical and horizontal layouts were applied to produce non-woven structures at all.

Keywords: tissue engineering, artificial scaffold, electrospinning, biocomposites

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Authors: Hamed Hedayatnia, Nathan Van Den Bossche

Abstract:

Understanding the ways in which climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the conservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like freeze-thaw cycles and wind erosion is also a key parameter when considering mitigating actions. Due to the vulnerability of cultural heritage to climate change, the impact of this phenomenon on material degradation criteria with the focus on brick masonry walls in Timurid heritage, located in Iran, was studied. The Timurids were the final great dynasty to emerge from the Central Asian steppe. Through their patronage, the eastern Islamic world in northwestern of Iran, especially in Mashhad and Herat, became a prominent cultural center. Goharshad Mosque is a mosque in Mashhad of the Razavi Khorasan Province, Iran. It was built by order of Empress Goharshad, the wife of Shah Rukh of the Timurid dynasty in 1418 CE. Choosing an appropriate regional climate model was the first step. The outputs of two different climate model: the 'ALARO-0' and 'REMO,' were analyzed to find out which model is more adopted to the area. For validating the quality of the models, a comparison between model data and observations was done in 4 different climate zones in Iran for a period of 30 years. The impacts of the projected climate change were evaluated until 2100. To determine the material specification of Timurid bricks, standard brick samples from a Timurid mosque were studied. Determination of water absorption coefficient, defining the diffusion properties and determination of real density, and total porosity tests were performed to characterize the specifications of brick masonry walls, which is needed for running HAM-simulations. Results from the analysis showed that the threatening factors in each climate zone are almost different, but the most effective factor around Iran is the extreme temperature increase and erosion. In the north-western region of Iran, one of the key factors is wind erosion. In the north, rainfall erosion and mold growth risk are the key factors. In the north-eastern part, in which our case study is located, the important parameter is wind erosion.

Keywords: brick, climate change, degradation criteria, heritage, Timurid period

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Authors: Abhishek Saha, Serene Tay, Gerard Pijcke

Abstract:

The availability of high-resolution topography and rainfall information in urban areas has made it necessary to revise modeling approaches used for simulating flood risk assessments. Lidar derived elevation models that have 1m or lower resolutions are becoming widely accessible. The classical approaches of 1D-2D flow models where channel flow is simulated and coupled with a coarse resolution 2D overland flow models may not fully utilize the information provided by high-resolution data. In this context, a study was undertaken to compare three different modeling approaches to simulate flooding in an urban area. The first model used is the base model used is Sobek, which uses 1D model formulation together with hydrologic boundary conditions and couples with an overland flow model in 2D. The second model uses a full 2D model for the entire area with shallow water equations at the resolution of the digital elevation model (DEM). These models are compared against another shallow water equation solver in 2D, which uses a subgrid method for grid refinement. These models are simulated for different horizontal resolutions of DEM varying between 1m to 5m. The results show a significant difference in inundation extents and water levels for different DEMs. They are also sensitive to the different numerical models with the same physical parameters, such as friction. The study shows the importance of having reliable field observations of inundation extents and levels before a choice of model and data can be made for spatial flood risk assessments.

Keywords: flooding, DEM, shallow water equations, subgrid

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Authors: Gurinder Singh Brar, Sarbjeet Singh, Harry Garg

Abstract:

Wire Electric Discharge Machining (WEDM) is thermal machining process capable of machining very hard electrically conductive material irrespective of their hardness. WEDM is being widely used to machine micro-scale parts with the high dimensional accuracy and surface finish. The objective of this paper is to optimize the process parameters of wire EDM to fabricate the microchannels and to calculate the surface finish and material removal rate of microchannels fabricated using wire EDM. The material used is aluminum 6061 alloy. The experiments were performed using CNC wire cut electric discharge machine. The effect of various parameters of WEDM like pulse on time (TON) with the levels (100, 150, 200), pulse off time (TOFF) with the levels (25, 35, 45) and current (IP) with the levels (105, 110, 115) were investigated to study the effect on output parameter i.e. Surface Roughness and Material Removal Rate (MRR). Each experiment was conducted under different conditions of a pulse on time, pulse off time and peak current. For material removal rate, TON and Ip were the most significant process parameter. MRR increases with the increase in TON and Ip and decreases with the increase in TOFF. For surface roughness, TON and Ip have the maximum effect and TOFF was found out to be less effective.

Keywords: microchannels, Wire Electric Discharge Machining (WEDM), Metal Removal Rate (MRR), surface finish

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

Abstract:

Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

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