Search results for: dimensional data model

Authors: Chen Zhang, Nan Chen

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High-dimensional process monitoring becomes increasingly important in many application domains, where usually the process distribution is unknown and much more complicated than the normal distribution, and the between-stream correlation can not be neglected. However, since the process dimension is generally much bigger than the reference sample size, most traditional nonparametric multivariate control charts fail in high-dimensional cases due to the curse of dimensionality. Furthermore, when the process goes out of control, the influenced variables are quite sparse compared with the whole dimension, which increases the detection difficulty. Targeting at these issues, this paper proposes a new nonparametric monitoring scheme for high-dimensional processes. This scheme first projects the high-dimensional process into several subprocesses using random projections for dimension reduction. Then, for every subprocess with the dimension much smaller than the reference sample size, a local nonparametric control chart is constructed based on the spatial rank test to detect changes in this subprocess. Finally, the results of all the local charts are fused together for decision. Furthermore, after an out-of-control (OC) alarm is triggered, a diagnostic framework is proposed. using the square-root LASSO. Numerical studies demonstrate that the chart has satisfactory detection power for sparse OC changes and robust performance for non-normally distributed data, The diagnostic framework is also effective to identify truly changed variables. Finally, a real-data example is presented to demonstrate the application of the proposed method.

Keywords: random projection, high-dimensional process control, spatial rank, sequential change detection

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Authors: Emad E. Abdallah, Alaa E. Abdallah, Bajes Y. Alskarnah

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We introduce a robust three-dimensional watermarking algorithm for copyright protection and indexing. The basic idea behind our technique is to measure the interquartile range or the spread of the 3D model vertices. The algorithm starts by converting all the vertices to spherical coordinate followed by partitioning them into small groups. The proposed algorithm is slightly altering the interquartile range distribution of the small groups based on predefined watermark. The experimental results on several 3D meshes prove perceptual invisibility and the robustness of the proposed technique against the most common attacks including compression, noise, smoothing, scaling, rotation as well as combinations of these attacks.

Keywords: watermarking, three-dimensional models, perceptual invisibility, interquartile range, 3D attacks

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Authors: Kwang Chun, John Kemeny

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Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

Procedia PDF Downloads 130

Authors: Saud Hassan

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This paper shows simulation for the prediction of the flow around the backlight angle of the passenger vehicle. The CFD simulations are carried out on different car models. The Ahmed model “bluff body” used as the stander model to study aerodynamics of the backlight angle. This paper described the airflow over the different car models with different backlight angles and also on the Ahmed model to determine the trailing vortices with the varying backlight angle of a passenger vehicle body. The CFD simulation is carried out with the Ahmed body which has simplified car model mainly used in automotive industry to investigate the flow over the car body surface. The main goal of the simulation is to study the behavior of trailing vortices of these models. In this paper the air flow over the slant angle of 0,5o, 12.5o, 20o, 30o, 40o are considered. As investigating on the rear backlight angle two dimensional flows occurred at the rear slant, on the other hand when the slant angle is 30o the flow become three dimensional. Above this angle sudden drop occurred in drag.

Keywords: aerodynamics, Ahemd vehicle , backlight angle, finite element method

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Authors: Michael Koblischka, Yassine Slimani, Thomas Karwoth, Anjela Koblischka-Veneva, Essia Hannachi

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On bulk FeSe superconductors containing different additions of Ag, a thorough investigation of the microstructures was performed using optical microscopy, SEM and TEM. The electrical resistivity was measured using four-point measurements in the temperature range 2 K ≤ T ≤ 150 K. The data obtained are analyzed in the framework of the excess conductivity approach using the Aslamazov-Larkin (AL) model. The investigated samples comprised of five distinct fluctuation regimes, namely short-wave (SWF), onedimensional (1D), two-dimensional (2D), three-dimensional (3D), and critical (CR) fluctuation regimes. The coherence length along the c-axis at zero-temperature (ξc(0)), the lower and upper critical magnetic fields (Bc1 and Bc2), the critical current density (Jc) and numerous other superconducting parameters were estimated with respect to the Ag content in the samples. The data reveal a reduction of the resistivity and a strong decrease of ξc(0) when doping the 11-samples with silver. The optimum content of the Ag-addition is found at 4 wt.-% Ag, yielding the highest critical current density.

Keywords: iron-based superconductors, FeSe, Ag-addition, excess conductivity, microstructure

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Authors: Ginger Egberts, Marianne Schaaphok, Fred Vermolen, Paul van Zuijlen

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A few years ago, a promising morphoelastic model was developed for the simulation of contraction formation after burn injuries. Contraction can lead to a serious reduction in physical mobility, like a reduction in the range-of-motion of joints. If this is the case in a healing burn wound, then this is referred to as a contracture that needs medical intervention. The morphoelastic model consists of a set of partial differential equations describing both a chemical part and a mechanical part in dermal wound healing. These equations are solved with the numerical finite element method (FEM). In this method, many calculations are required on each of the chosen elements. In general, the more elements, the more accurate the solution. However, the number of elements increases rapidly if simulations are performed in 2D and 3D. In that case, it not only takes longer before a prediction is available, the computation also becomes more expensive. It is therefore important to investigate alternative possibilities to generate the same results, based on the input parameters only. In this study, a surrogate neural network has been designed to mimic the results of the one-dimensional morphoelastic model. The neural network generates predictions quickly, is easy to implement, and there is freedom in the choice of input and output. Because a neural network requires extensive training and a data set, it is ideal that the one-dimensional FEM code generates output quickly. These feed-forward-type neural network results are very promising. Not only can the network give faster predictions, but it also has a performance of over 99%. It reports on the relative surface area of the wound/scar, the total strain energy density, and the evolutions of the densities of the chemicals and mechanics. It is, therefore, interesting to investigate the applicability of a neural network for the two- and three-dimensional morphoelastic model for contraction after burn injuries.

Keywords: biomechanics, burns, feasibility, feed-forward NN, morphoelasticity, neural network, relative surface area wound

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Authors: Samira Cherid, Samir Bentata, F. Zahira Meghoufel, Sabria Terkhi, Yamina Sefir, Fatima Bendahma, Bouabdellah Bouadjemi, Ali Z. Itouni

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In this work, we examined the propagation of light in one-dimensional systems is examined by means of the random dimer model. The introduction of defect elements, randomly in the studied system, breaks down the Anderson localization and provides a set of propagating delocalized modes at the corresponding conventional dimer resonances. However, tuning suitably the defect dimer resonance on the host ones (or vice versa), the transmission magnitudes can be enhanced providing the optimized ballistic transmission regime as an average response. Hence, ballistic optical filters can be conceived at desired wavelengths.

Keywords: photonic crystals, random dimer model, ballistic resonance, localization and transmission

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Arif Ali, Divya Raj Sapkota

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In this paper, we explain gravitational attraction as the consequence of the dynamics of four-dimensional bodies and the consequent distortion of space. This approach provides an alternative direction to understand various physical phenomena based on the existence of the fourth spatial dimension. For this interpretation, we formulate the acceleration due to gravity and orbital velocity based on the accelerating expansion of three-dimensional symmetric bodies. It is also shown how distortion in space caused by the dynamics of four-dimensional bodies counterbalances the effect of expansion. We find that the motion of four-dimensional bodies through four-dimensional space leads to gravitational attraction, and the expansion of bodies leads to surface gravity. Thus, dynamics in the fourth spatial dimension provide an alternative explanation to gravity.

Keywords: dimensions, four, gravity, voluceleration

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Authors: Zubier Arfan, Paul Johnson

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The electronification of financial markets and the rise of algorithmic trading has sparked a lot of interest from the mathematical community, for the market making-problem in particular. The research presented in this short paper solves the classic stochastic control problem in order to derive the strategy for a market-maker. It also shows how to calibrate and simulate the strategy with real limit order book data for back-testing. The ambiguity of limit-order priority in back-testing is dealt with by considering optimistic and pessimistic priority scenarios. The model, although it does outperform a naive strategy, assumes constant volatility, therefore, is not best suited to the LOB data. The Heston model is introduced to describe the price and variance process of the asset. The Trader's constant absolute risk aversion utility function is optimised by numerically solving a 3-dimensional Hamilton-Jacobi-Bellman partial differential equation to find the optimal limit order quotes. The results show that the stochastic volatility market-making model is more suitable for a risk-averse trader and is also less sensitive to calibration error than the constant volatility model.

Keywords: market-making, market-microsctrucure, stochastic volatility, quantitative trading

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Authors: Mateus Silva Mendonça, Wender Pereira de Oliveira, Gabriel Heleno de Paula Araújo, Hiago Tenório Teixeira Santana Rocha, Augusto César Teixeira Malaquias, José Guilherme Coelho Baeta

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The stricter legislation and the greater demand of the population regard to gas emissions and their effects on the environment as well as on human health make the automotive industry reinforce research focused on reducing levels of contamination. This reduction can be achieved through the implementation of improvements in internal combustion engines in such a way that they promote the reduction of both specific fuel consumption and air pollutant emissions. These improvements can be obtained through numerical simulation, which is a technique that works together with experimental tests. The aim of this paper is to build, with support of the GT-Suite software, a one-dimensional model of a single-cylinder research engine to analyze the impact of the variation of swirl and tumble coefficients on the performance and on the air pollutant emissions of an engine. Initially, the discharge coefficient is calculated through the software Converge CFD 3D, given that it is an input parameter in GT-Power. Mesh sensitivity tests are made in 3D geometry built for this purpose, using the mass flow rate in the valve as a reference. In the one-dimensional simulation is adopted the non-predictive combustion model called Three Pressure Analysis (TPA) is, and then data such as mass trapped in cylinder, heat release rate, and accumulated released energy are calculated, aiming that the validation can be performed by comparing these data with those obtained experimentally. Finally, the swirl and tumble coefficients are introduced in their corresponding objects so that their influences can be observed when compared to the results obtained previously.

Keywords: 1D simulation, single-cylinder research engine, swirl coefficient, three pressure analysis, tumble coefficient

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Authors: Ehsan Sakhaei, Ali Taherabadi

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In this study, an aft sweep wing with specific characteristic feature was analysis with CFD method in Fluent software. In this analysis wings aerodynamic coefficient was calculated in different rake angle and wing lift curve slope to rake angle was achieved. Wing section was selected among NACA airfoils version 6. The sweep angle of wing is 15 degree, aspect ratio 8 and taper ratios 0.4. Designing and modeling this wing was done in CATIA software. This model was meshed in Gambit software and its three dimensional analysis was done in Fluent software. CFD methods used here were based on pressure base algorithm. SIMPLE technique was used for solving Navier-Stokes equation and Spalart-Allmaras model was utilized to simulate three dimensional wing in air. Roskam method is one of the common and most used methods for determining aerodynamics parameters in the field of airplane designing. In this study besides CFD analysis, an advanced aircraft analysis was used for calculating aerodynamic coefficient using Roskam method. The results of CFD were compared with measured data acquired from Roskam method and authenticity of relation was evaluated. The results and comparison showed that in linear region of lift curve there is a minor difference between aerodynamics parameter acquired from CFD to relation present by Roskam.

Keywords: aft sweep wing, CFD method, fluent, Roskam, Spalart-Allmaras model

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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Authors: Femy M. Makkar, S. Chandrakaran, N. Sankar

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The concept of reinforced earth has been used in the field of geotechnical engineering since 1960s, for many applications such as, construction of road and rail embankments, pavements, retaining walls, shallow foundations, soft ground improvement and so on. Conventionally, planar geosynthetic materials such as geotextiles and geogrids were used as the reinforcing elements. Recently, the use of three dimensional reinforcements becomes one of the emerging trends in this field. So, in the present investigation, three dimensional geogrid is proposed as a reinforcing material. Laboratory scaled plate load tests are conducted on a model square footing resting on 3D geogrid reinforced sand bed. The performance of 3D geogrids in triangular and square pattern was compared with conventional geogrids and the improvement in bearing capacity and reduction in settlement and heave are evaluated. When single layer of reinforcement was placed at an optimum depth of 0.25B from the bottom of the footing, the bearing capacity of conventional geogrid reinforced soil improved by 1.85 times compared to unreinforced soil, where as 3D geogrid reinforced soil with triangular pattern and square pattern shows 2.69 and 3.05 times improvement respectively compared to unreinforced soil. Also, 3D geogrids performs better than conventional geogrids in reducing the settlement and heave of sand bed around the model footing.

Keywords: 3D reinforcing elements, bearing capacity, heavy, settlement

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Authors: Julia Desiree Velastegui Caceres, Luis Alejandro Velastegui Caceres, Oswaldo Padilla, Eduardo Kirby, Francisco Guerrero, Theofilos Toulkeridis

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It is fundamental to conserve sites of natural and cultural heritage with any available technique or existing methodology of preservation in order to sustain them for the following generations. We propose a further skill to protect the actual view of such sites, in which with high technology instrumentation we are able to digitally preserve natural and cultural heritages applied in Ecuador. In this project the use of laser technology is presented for three-dimensional models, with high accuracy in a relatively short period of time. In Ecuador so far, there are not any records on the use and processing of data obtained by this new technological trend. The importance of the project is the description of the methodology of the laser scanner system using the Faro Laser Scanner Focus 3D 120, the method for 3D modeling of geospatial data and the development of virtual environments in the areas of Cultural and Natural Heritage. In order to inform users this trend in technology in which three-dimensional models are generated, the use of such tools has been developed to be able to be displayed in all kinds of digitally formats. The results of the obtained 3D models allows to demonstrate that this technology is extremely useful in these areas, but also indicating that each data campaign needs an individual slightly different proceeding starting with the data capture and processing to obtain finally the chosen virtual environments.

Keywords: laser scanner system, 3D model, cultural heritage, natural heritage

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Authors: Alireza Dantism

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Presently, describing the function of a protein sequence is one of the most common problems in biology. Usually, this problem can be facilitated by studying the three-dimensional structure of proteins. In the absence of a protein structure, comparative modeling often provides a useful three-dimensional model of the protein that is dependent on at least one known protein structure. Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) mainly based on its alignment with one or more proteins of known structure (templates). Comparative modeling consists of four main steps 1. Similarity between the target sequence and at least one known template structure 2. Alignment of target sequence and template(s) 3. Build a model based on alignment with the selected template(s). 4. Prediction of model errors 5. Optimization of the built model There are many computer programs and web servers that automate the comparative modeling process. One of the most important advantages of these servers is that it makes comparative modeling available to both experts and non-experts, and they can easily do their own modeling without the need for programming knowledge, but some other experts prefer using programming knowledge and do their modeling manually because by doing this they can maximize the accuracy of their modeling. In this study, a web-based tool has been designed to predict the tertiary structure of proteins using PHP and Python programming languages. This tool is called EasyModel. EasyModel can receive, according to the user's inputs, the desired unknown sequence (which we know as the target) in this study, the protein sequence file (template), etc., which also has a percentage of similarity with the primary sequence, and its third structure Predict the unknown sequence and present the results in the form of graphs and constructed protein files.

Keywords: structural bioinformatics, protein tertiary structure prediction, modeling, comparative modeling, modeller

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Authors: S. J. M. Mohd Saleh, S. Guo

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Composite materials have become an important option for the primary structure of aircraft due to their design flexibility and ability to improve the overall performance. At present, the option for composite usage in aircraft component is largely based on experience, knowledge, benchmarking and partly market driven. An inevitable iterative design during the design stage and validation process will increase the development time and cost. This paper aims at presenting the correlation between laminate and composite thin-wall beam structure, which contains the theoretical and numerical investigations on stiffness estimation of composite aerostructures with applications to aircraft wings. Classical laminate theory and thin-walled beam theory were applied to define the correlation between 1-dimensional composite laminate and 2-dimensional composite beam structure, respectively. Then FE model was created to represent the 3-dimensional structure. A detailed study on stiffness matrix of composite laminates has been carried out to understand the effects of stacking sequence on the coupling between extension, shear, bending and torsional deformation of wing box structures for 1-dimensional, 2-dimensional and 3-dimensional structures. Relationships amongst composite laminates and composite wing box structures of the same material have been developed in this study. These correlations will be guidelines for the design engineers to predict the stiffness of the wing box structure during the material selection process and laminate design stage.

Keywords: aircraft design, aircraft structures, classical lamination theory, composite structures, laminate theory, structural design, thin-walled beam theory, wing box design

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Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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Authors: Luma Al-Tamimi, Hassan Farhat, Wessam Hasan

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A three-dimensional (3D) hybrid quasi-steady thermal lattice Boltzmann model is developed to couple the effects of surfactant, temperature, interfacial tension, and contact angle. This 3D model is an extended scheme of a previously introduced two-dimensional (2D) hybrid lattice Boltzmann model. The 3D model is used to study the combined multi-physics effects on emulsion systems flowing in rectangular microchannels with and without confinements, where the suspended phase is made of droplets, plugs, or a mixture of both. The simulation results show that emulsion systems with plugs as the suspended phase are more efficient than with droplets, whereas mixed systems that form large plugs through coalescence have even greater efficiency. The 3D contact angle model generates matching results to those of the 2D model, which were validated with experiments. Furthermore, the effects of various confinements on adhering single drop systems are investigated for delineating their influence on the power required for transporting the suspended phase through the channel. It is shown that the deeper the constriction is, the lower the system efficiency. Increasing the surfactant concentration or fluid temperature in a channel with confinement carries a substantial positive effect on oil droplet transportation.

Keywords: lattice Boltzmann method, thermal, contact angle, surfactants, high viscosity ratio, porous media

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Authors: Xi Gu, Guan Heng Yeoh, Victoria Timchenko

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In the current work, a three-dimensional geometry of a 75% stenosed blood vessel is analysed. Large eddy simulation (LES) with the help of a dynamic subgrid scale Smagorinsky model is applied to model the turbulent pulsatile flow. The geometry, the transmural pressure and the properties of the blood and the elastic boundary were based on clinical measurement data. For the flexible wall model, a thin solid region is constructed around the 75% stenosed blood vessel. The deformation of this solid region was modelled as a deforming boundary to reduce the computational cost of the solid model. Fluid-structure interaction is realised via a two-way coupling between the blood flow modelled via LES and the deforming vessel. The information of the flow pressure and the wall motion was exchanged continually during the cycle by an arbitrary lagrangian-eulerian method. The boundary condition of current time step depended on previous solutions. The fluctuation of the velocity in the post-stenotic region was analysed in the study. The axial velocity at normalised position Z=0.5 shows a negative value near the vessel wall. The displacement of the elastic boundary was concerned in this study. In particular, the wall displacement at the systole and the diastole were compared. The negative displacement at the stenosis indicates a collapse at the maximum velocity and the deceleration phase.

Keywords: Large Eddy Simulation, Fluid Structural Interaction, constricted artery, Computational Fluid Dynamics

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Authors: M. A. Fiidow, Ahmad M. Alenezi

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In this work, we study the inner derivations of diassociative algebras in dimension two and three, an algorithmic approach is adopted for the computation of inner derivation, using some results from the derivation of finite dimensional diassociative algebras. Some basic properties of inner derivation of finite dimensional diassociative algebras are also provided.

Keywords: diassociative algebras, inner derivations, derivations, left and right operator

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Authors: Fatemah A. Alqallaf, Debasis Kundu

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The aim of this paper is to introduce a bivariate inverse generalized exponential distribution which has a singular component. The proposed bivariate distribution can be used when the marginals have heavy-tailed distributions, and they have non-monotone hazard functions. Due to the presence of the singular component, it can be used quite effectively when there are ties in the data. Since it has four parameters, it is a very flexible bivariate distribution, and it can be used quite effectively for analyzing various bivariate data sets. Several dependency properties and dependency measures have been obtained. The maximum likelihood estimators cannot be obtained in closed form, and it involves solving a four-dimensional optimization problem. To avoid that, we have proposed to use an EM algorithm, and it involves solving only one non-linear equation at each `E'-step. Hence, the implementation of the proposed EM algorithm is very straight forward in practice. Extensive simulation experiments and the analysis of one data set have been performed. We have observed that the proposed bivariate inverse generalized exponential distribution can be used for modeling dependent competing risks data. One data set has been analyzed to show the effectiveness of the proposed model.

Keywords: Block and Basu bivariate distributions, competing risks, EM algorithm, Marshall-Olkin bivariate exponential distribution, maximum likelihood estimators

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Authors: Bouabdellah Abed, Mohamed Bouzit, Lakhdar Bouarbi

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The objective of this study is to investigate numerically the effect of roof shaped on wind flow and pollutant dispersion in a street canyon with one row of trees of pore volume, Pvol = 96%. A three-dimensional computational fluid dynamics (CFD) model for evaluating air flow and pollutant dispersion within an urban street canyon using Reynolds-averaged Navier–Stokes (RANS) equations and the k-Epsilon EARSM turbulence model as close of the equation system. The numerical model is performed with ANSYS-CFX code. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated against the wind tunnel experiment. Having established this, the wind flow and pollutant dispersion in urban street canyons of six roof shapes are simulated. The numerical simulation agrees reasonably with the wind tunnel data. The results obtained in this work, indicate that the flow in 3D domain is more complicated, this complexity is increased with presence of tree and variability of the roof shapes. The results also indicated that the largest pollutant concentration level for two walls (leeward and windward wall) is observed with the upwind wedge-shaped roof. But the smallest pollutant concentration level is observed with the dome roof-shaped. The results also indicated that the corners eddies provide additional ventilation and lead to lower traffic pollutant concentrations at the street canyon ends.

Keywords: street canyon, pollutant dispersion, trees, building configuration, numerical simulation, k-Epsilon EARSM

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Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

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Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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Authors: H. Al-Hajeri

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The computation of the effectiveness of turbulence enhancement surface features, such as ribs as means of promoting mixing and hence heat transfer, has attracted the continued attention of the engineering community. In this study, the simulation of a three-dimensional cooling passage is carried out employing a number of turbulence models including Durbin model. The cooling passage consists of a square section duct whose upper and lower surfaces feature staggered cuboid ribs. The main objective of this paper is to provide comparisons of the performance of the v2-f model against other established turbulence models as implemented in the commercial CFD code Ansys Fluent. The present study demonstrates that the v2-f model can successfully capture the isothermal air flow phenomena in flow over obstacles.

Keywords: CFD, cooling passage, Durbin model, turbulence model

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Authors: Muhammad Sohail Khan, Rehan Ali Shah

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The present paper applies the optimal homotopy perturbation method (OHPM) and the optimal homotopy asymptotic method (OHAM) introduced recently to obtain analytic approximations of the non-linear equations modeling the flow of polymer in case of wire coating of a corotational Maxwell fluid. Expression for the velocity field is obtained in non-dimensional form. Comparison of the results obtained by the two methods at different values of non-dimensional parameter l₁₀, reveal that the OHPM is more effective and easy to use. The OHPM solution can be improved even working in the same order of approximation depends on the choices of the auxiliary functions.

Keywords: corotational Maxwell model, optimal homotopy asymptotic method, optimal homotopy perturbation method, wire coating die

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Authors: Ouzayr Rabhi, Ibtissam Arrassen

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To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

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Authors: hadi kargar, bahador shabani

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In this article, 16 cylinder motor combustion CFD modeling with a diameter of 165 mm and 195 mm along the way to help the FIRE software to optimize its function to work. A three-dimensional model of the processes that formed inside the cylinder made that involves mixing the fuel and air, ignition and spraying. In this three-dimensional model, all chemical species, density of air fuel spraying and spray with full profile intended to detailed results from mixing the fuel and air, igniting the ignition advance, spray, and mixed media in different times and get fit by moving the piston. Optimal selection of the model for the shape of the piston and spraying fuel specifications (including the management of spraying, the number of azhneh hole, start time of spraying and spraying angle) to achieve the best fuel consumption and minimal pollution. The spray hole 6 and 7 in three different configurations with five spraying and gives the best geometry and various performances in the simulation. 6 hole spray angle, finally spraying 72.5 degrees and two forms of spraying a better performance in comparison with other items of their own.

Keywords: spray, FIRE, CFD, optimize, diesel engine

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Authors: Monica Lia

Abstract:

This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Aijuka Nicholas

Abstract:

A research study was undertaken to characterize the aquifers and identify the potential groundwater recharge zones in the Kagandi district. Quantitative characterization of hydraulic conductivities of aquifers is of fundamental importance to the study of groundwater flow and contaminant transport in aquifers. A conditional approach is used to represent the spatial variability of hydraulic conductivity. Briefly, it involves using qualitative and quantitative geologic borehole-log data to generate a three-dimensional (3D) hydraulic conductivity distribution, which is then adjusted through calibration of a 3D groundwater flow model using pumping-test data and historic hydraulic data. The approach consists of several steps. The study area was divided into five sub-watersheds on the basis of artificial drainage divides. A digital terrain model (DTM) was developed using Arc GIS to determine the general drainage pattern of Kagandi watershed. Hydrologic characterization involved the determination of the various hydraulic properties of the aquifers. Potential groundwater recharge zones were identified by integrating various thematic maps pertaining to the digital elevation model, land use, and drainage pattern in Arc GIS and Sufer golden software. The study demonstrates the potential of GIS in delineating groundwater recharge zones and that the developed methodology will be applicable to other watersheds in Uganda.

Keywords: aquifers, Arc GIS, groundwater recharge, recharge zones

Procedia PDF Downloads 115