Search results for: Dimensional Modeling

Authors: Ashkan Shafee, Ahmad Fahimifar

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There is a growing demand for construction of high-rise buildings and infrastructures in large cities, which sometimes require deep excavations in the vicinity of pile foundations. In this study, a two-dimensional finite element analysis is used to gain insight into the response of pile groups adjacent to deep excavations in sand. The numerical code was verified by available experimental works, and a parametric study was performed on different working load combinations, excavation depth and supporting system. The results show that the simple two-dimensional plane strain model can accurately simulate the excavation induced changes on adjacent pile groups. It was found that further excavation than pile toe level and also inclined loading on adjacent pile group can severely affect the serviceability of the foundation.

Keywords: Deep excavation, pile group, inclined loading, lateral deformation.

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Authors: Bunakiye R. Japheth, Ogude U. Cyril

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

Keywords: Control process, metrics of engineering, structured abstraction, semantic model.

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Authors: Mohd Azrul Hisham Mohd Adib, Nur Hazreen Mohd Hasni

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A three-dimensional and pulsatile blood flow in the left ventricle of heart model has been studied numerically. The geometry was derived from a simple approximation of the left ventricle model and the numerical simulations were obtained using a formulation of the Navier-Stokes equations. In this study, simulation was used to investigate the pattern of flow velocity in 3D model of heart with consider the left ventricle based on critical parameter of blood under steady condition. Our results demonstrate that flow velocity focused from mitral valve channel and continuous linearly to left ventricle wall but this skewness progresses into outside wall in atrium through aortic valve with random distribution that is irregular due to force subtract from ventricle wall during cardiac cycle. The findings are the prediction of the behavior of the blood flow velocity pattern in steady flow condition which can assist the medical practitioners in their decision on the patients- treatments.

Keywords: Mitral Valve, Aortic Valve, Cardiac Cycle, Leaflet, Biomechanics, Left Ventricle

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Authors: R. Damaševičius

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System-level design based on high-level abstractions is becoming increasingly important in hardware and embedded system design. This paper analyzes meta-design techniques oriented at developing meta-programs and meta-models for well-understood domains. Meta-design techniques include meta-programming and meta-modeling. At the programming level of design process, metadesign means developing generic components that are usable in a wider context of application than original domain components. At the modeling level, meta-design means developing design patterns that describe general solutions to the common recurring design problems, and meta-models that describe the relationship between different types of design models and abstractions. The paper describes and evaluates the implementation of meta-design in hardware design domain using object-oriented and meta-programming techniques. The presented ideas are illustrated with a case study.

Keywords: Design patterns, meta-design, meta-modeling, metaprogramming.

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Authors: Chi-Lun Liu

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Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.

Keywords: Knowledge representation, reasoning, ontology, class diagram, software engineering.

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Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

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Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular / nanoscale models is demonstrated.

Keywords: Cement composite, Mechanical Properties, Molecular Dynamics, Plasticizer additives.

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Authors: Lana Dalawr Jalal

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This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex threedimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: Obstacle Avoidance, Particle Swarm Optimization, Three-Dimensional Path Planning Unmanned Aerial Vehicles.

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Authors: Damian Ramajo, Santiago Corzo, Norberto Nigro

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A Multi-dimensional computational fluid dynamics (CFD) two-phase model was developed with the aim to simulate the in-core coolant circuit of a pressurized heavy water reactor (PHWR) of a commercial nuclear power plant (NPP). Due to the fact that this PHWR is a Reactor Pressure Vessel type (RPV), three-dimensional (3D) detailed modelling of the large reservoirs of the RPV (the upper and lower plenums and the downcomer) were coupled with an in-house finite volume one-dimensional (1D) code in order to model the 451 coolant channels housing the nuclear fuel. Regarding the 1D code, suitable empirical correlations for taking into account the in-channel distributed (friction losses) and concentrated (spacer grids, inlet and outlet throttles) pressure losses were used. A local power distribution at each one of the coolant channels was also taken into account. The heat transfer between the coolant and the surrounding moderator was accurately calculated using a two-dimensional theoretical model. The implementation of subcooled boiling and condensation models in the 1D code along with the use of functions for representing the thermal and dynamic properties of the coolant and moderator (heavy water) allow to have estimations of the in-core steam generation under nominal flow conditions for a generic fission power distribution. The in-core mass flow distribution results for steady state nominal conditions are in agreement with the expected from design, thus getting a first assessment of the coupled 1/3D model. Results for nominal condition were compared with those obtained with a previous 1/3D single-phase model getting more realistic temperature patterns, also allowing visualize low values of void fraction inside the upper plenum. It must be mentioned that the current results were obtained by imposing prescribed fission power functions from literature. Therefore, results are showed with the aim of point out the potentiality of the developed model.

Keywords: CFD, PHWR, Thermo-hydraulic, Two-phase flow.

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Authors: Samy E. Oraby, Ayman M. Alaskari

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The importance of machining process in today-s industry requires the establishment of more practical approaches to clearly represent the intimate and severe contact on the tool-chipworkpiece interfaces. Mathematical models are developed using the measured force signals to relate each of the tool-chip friction components on the rake face to the operating cutting parameters in rough turning operation using multilayers coated carbide inserts. Nonlinear modeling proved to have high capability to detect the nonlinear functional variability embedded in the experimental data. While feedrate is found to be the most influential parameter on the friction coefficient and its related force components, both cutting speed and depth of cut are found to have slight influence. Greater deformed chip thickness is found to lower the value of friction coefficient as the sliding length on the tool-chip interface is reduced.

Keywords: Mathematical modeling, Cutting forces, Frictionforces, Friction coefficient and Chip ratio.

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Authors: Vinay Chandwani, Vinay Agrawal, Ravindra Nagar

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Artificial Neural Networks (ANN) trained using backpropagation (BP) algorithm are commonly used for modeling material behavior associated with non-linear, complex or unknown interactions among the material constituents. Despite multidisciplinary applications of back-propagation neural networks (BPNN), the BP algorithm possesses the inherent drawback of getting trapped in local minima and slowly converging to a global optimum. The paper present a hybrid artificial neural networks and genetic algorithm approach for modeling slump of ready mix concrete based on its design mix constituents. Genetic algorithms (GA) global search is employed for evolving the initial weights and biases for training of neural networks, which are further fine tuned using the BP algorithm. The study showed that, hybrid ANN-GA model provided consistent predictions in comparison to commonly used BPNN model. In comparison to BPNN model, the hybrid ANNGA model was able to reach the desired performance goal quickly. Apart from the modeling slump of ready mix concrete, the synaptic weights of neural networks were harnessed for analyzing the relative importance of concrete design mix constituents on the slump value. The sand and water constituents of the concrete design mix were found to exhibit maximum importance on the concrete slump value.

Keywords: Artificial neural networks, Genetic algorithms, Back-propagation algorithm, Ready Mix Concrete, Slump value.

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Authors: Alicia Y. C. Tang, Rukaini Abdullah, Sharifuddin M. Zain, Noorsaadah A. Rahman

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This paper discusses the causal explanation capability of QRIOM, a tool aimed at supporting learning of organic chemistry reactions. The development of the tool is based on the hybrid use of Qualitative Reasoning (QR) technique and Qualitative Process Theory (QPT) ontology. Our simulation combines symbolic, qualitative description of relations with quantity analysis to generate causal graphs. The pedagogy embedded in the simulator is to both simulate and explain organic reactions. Qualitative reasoning through a causal chain will be presented to explain the overall changes made on the substrate; from initial substrate until the production of final outputs. Several uses of the QPT modeling constructs in supporting behavioral and causal explanation during run-time will also be demonstrated. Explaining organic reactions through causal graph trace can help improve the reasoning ability of learners in that their conceptual understanding of the subject is nurtured.

Keywords: Qualitative reasoning, causal graph, organicreactions, explanation, QPT, modeling constructs.

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Authors: Vijay Kumar Kukreja, Ravneet Kaur

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In this paper, one dimensional advection diffusion model is analyzed using finite difference method based on Crank-Nicolson scheme. A practical problem of filter cake washing of chemical engineering is analyzed. The model is converted into dimensionless form. For the grid Ω × ω = [0, 1] × [0, T], the Crank-Nicolson spatial derivative scheme is used in space domain and forward difference scheme is used in time domain. The scheme is found to be unconditionally convergent, stable, first order accurate in time and second order accurate in space domain. For a test problem, numerical results are compared with the analytical ones for different values of parameter.

Keywords: Consistency, Crank-Nicolson scheme, Gerschgorin circle, Lax-Richtmyer theorem, Peclet number, stability.

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Authors: Shingo Murakami, Shinichi Enoki

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In structures, stress concentration is a factor of fatigue fracture. Basically, the stress concentration is a phenomenon that should be avoided. However, it is difficult to avoid the stress concentration. Therefore, relaxation of the stress concentration is important. The stress concentration arises from notches and circular holes. There is a relaxation method that a composite patch covers a notch and a circular hole. This relaxation method is used to repair aerial wings, but it is not systematized. Composites are more expensive than single materials. Accordingly, we propose the relaxation method that a single material patch covers a notch and a circular hole, and aim to systematize this relaxation method. We performed FEA (Finite Element Analysis) about an object by using a three-dimensional FEA model. The object was that a patch adheres to a plate with a circular hole. And, a uniaxial tensile load acts on the patched plate with a circular hole. In the three-dimensional FEA model, it is not easy to model the adhesion layer. Basically, the yield stress of the adhesive is smaller than that of adherents. Accordingly, the adhesion layer gets to plastic deformation earlier than the adherents under the yield load of adherents. Therefore, we propose the three-dimensional FEA model which is applied a nonlinear elastic region to the adhesion layer. The nonlinear elastic region was calculated by a bilinear approximation. We compared the analysis results with the tensile test results to confirm whether the analysis model has usefulness. As a result, the analysis results agreed with the tensile test results. And, we confirmed that the analysis model has usefulness. As a result that the three-dimensional FEA model was used to the analysis, it was confirmed that an out-of-plane deformation occurred to the patched plate with a circular hole. The out-of-plane deformation causes stress increase of the patched plate with a circular hole. Therefore, we investigated that the out-of-plane deformation affects relaxation of the stress concentration in the plate with a circular hole on this relaxation method. As a result, it was confirmed that the out-of-plane deformation inhibits relaxation of the stress concentration on the plate with a circular hole.

Keywords: Stress concentration, patch, out-of-plane deformation, Finite Element Analysis.

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Authors: G. Zahedi, H. Yaghoobi

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Modeling of a heterogeneous industrial fixed bed reactor for selective dehydrogenation of heavy paraffin with Pt-Sn- Al2O3 catalyst has been the subject of current study. By applying mass balance, momentum balance for appropriate element of reactor and using pressure drop, rate and deactivation equations, a detailed model of the reactor has been obtained. Mass balance equations have been written for five different components. In order to estimate reactor production by the passage of time, the reactor model which is a set of partial differential equations, ordinary differential equations and algebraic equations has been solved numerically. Paraffins, olefins, dienes, aromatics and hydrogen mole percent as a function of time and reactor radius have been found by numerical solution of the model. Results of model have been compared with industrial reactor data at different operation times. The comparison successfully confirms validity of proposed model.

Keywords: Dehydrogenation, fixed bed reactor, modeling, linear alkyl benzene.

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Authors: G. Candel, D. Naccache

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t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embedding. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic, and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n2) to O(n2/k), and the memory requirement from n2 to 2(n/k)2 which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: Concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning.

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Authors: G.Kabashi, K.Kadriu, A.Gashi, S.Kabashi, G, Pula, V.Komoni

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This paper focuses on PSS/E modeling of wind farms of Doubly-fed Induction Generator (DFIG) type and their impact on issues of power system operation. Since Wind Turbine Generators (WTG) don-t have the same characteristics as synchronous generators, the appropriate modeling of wind farms is essential for transmission system operators to analyze the best options of transmission grid reinforcements as well as to evaluate the wind power impact on reliability and security of supply. With the high excepted penetration of wind power into the power system a simultaneous loss of Wind Farm generation will put at risk power system security and reliability. Therefore, the main wind grid code requirements concern the fault ride through capability and frequency operation range of wind turbines. In case of grid faults wind turbines have to supply a definite reactive power depending on the instantaneous voltage and to return quickly to normal operation.

Keywords: Power System transients, PSS/E dynamic simulationDouble-fed Induction Generator.

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Authors: Thitiporn Supasri, Natanee Vorayos, Piriya Thongchiew

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Electrification is a complex process and governed by various parameters.  Modeling of power plant’s target efficiency or target heat rate is often formulated and compared with the actual values. This comparison not only implies the performance of the power plant but also reflects the energy losses possibly inherited in some of related equipment and processes. The current modeling of Coal-fired Mae Moh power plant was formulated at the first commissioning. Some of equipments were replaced due to its life time. Relatively outdated for 20 years, the utilization of the model is not accomplished. This work has focused on the development of the performance analysis model of aforementioned power plant according to the most updated and current working conditions. The model is more appropriate and shows accuracy in its analysis.  Losses are detected and measures are introduced such that reduction in energy consumption, related cost, and also environment impacts can be anticipated.

Keywords: Performance analysis model, Power plant modeling, Target heat rate, Target efficiency.

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Authors: Mandhapati P. Raju, Siddhartha Khaitan

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In-core memory requirement is a bottleneck in solving large three dimensional Navier-Stokes finite element problem formulations using sparse direct solvers. Out-of-core solution strategy is a viable alternative to reduce the in-core memory requirements while solving large scale problems. This study evaluates the performance of various out-of-core sequential solvers based on multifrontal or supernodal techniques in the context of finite element formulations for three dimensional problems on a Windows platform. Here three different solvers, HSL_MA78, MUMPS and PARDISO are compared. The performance of these solvers is evaluated on a 64-bit machine with 16GB RAM for finite element formulation of flow through a rectangular channel. It is observed that using out-of-core PARDISO solver, relatively large problems can be solved. The implementation of Newton and modified Newton's iteration is also discussed.

Keywords: Out-of-core, PARDISO, MUMPS, Newton.

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Authors: Javad Khazaei, Rick S. Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: Consensus tracking, distributed control, model-free control, sparse identification of dynamical systems.

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Authors: Brajesh Kumar Jha, Neeru Adlakha, M. N. Mehta

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Mathematical and computational modeling of calcium signalling in nerve cells has produced considerable insights into how the cells contracts with other cells under the variation of biophysical and physiological parameters. The modeling of calcium signaling in astrocytes has become more sophisticated. The modeling effort has provided insight to understand the cell contraction. Main objective of this work is to study the effect of voltage gated (Operated) calcium channel (VOC) on calcium profile in the form of advection diffusion equation. A mathematical model is developed in the form of advection diffusion equation for the calcium profile. The model incorporates the important physiological parameter like diffusion coefficient etc. Appropriate boundary conditions have been framed. Finite volume method is employed to solve the problem. A program has been developed using in MATLAB 7.5 for the entire problem and simulated on an AMD-Turion 32-bite machine to compute the numerical results.

Keywords: Ca2+ Profile, Advection Diffusion, VOC, FVM.

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Authors: W. K. Yap, V. Karri

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This paper presents a hybrid electric scooter model developed and simulated using Matlab/Simulink. This hybrid scooter modeled has a parallel hybrid structure. The main propulsion units consist of a two stroke internal combustion engine and a hub motor attached to the front wheel of the scooter. The methodology used to optimize the energy and fuel consumption of the hybrid electric scooter is the multi-mode approach. Various case studies were presented to check the model and were compared to the literatures. Results shown that the model developed was feasible and valuable.

Keywords: Hybrid electric scooters, modeling and simulation, hybrid scooter energy management.

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Authors: Kimia Khoshdel Vajari, Saber Saffar

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Reducing the residual stresses caused by welding is desirable for the industry. The effect of welding sequence, as well as the effect of yield stress on the number of residual stresses generated in Inconel X750 superalloy sheets and beams, have been investigated. The finite element model used in this research is a three-dimensional thermal and mechanical model, and the type of analysis is indirect coupling. This analysis is done in two stages. First, thermal analysis is performed, and then the thermal changes of the first analysis are used as the applied load in the second analysis. ABAQUS has been used for modeling, and the Dflux subroutine has been used in the Fortran programming environment to move the arc and the molten pool. The results of this study show that the amount of tensile residual stress in symmetric, discontinuous, and symmetric-discontinuous welds is reduced to a maximum of 27%, 54%, and 37% compared to direct welding, respectively. The results also show that the amount of residual stresses created by welding increases linearly with increasing yield stress with a slope of 40%.

Keywords: Residual stress, X750 superalloy, finite element, welding, thermal analysis.

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Authors: O. Ejale, N.B. Siddique, R. Seals

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The purpose of this study was to present a reliable mean for human-computer interfacing based on finger gestures made in two dimensions, which could be interpreted and adequately used in controlling a remote robot's movement. The gestures were captured and interpreted using an algorithm based on trigonometric functions, in calculating the angular displacement from one point of touch to another as the user-s finger moved within a time interval; thereby allowing for pattern spotting of the captured gesture. In this paper the design and implementation of such a gesture based user interface was presented, utilizing the aforementioned algorithm. These techniques were then used to control a remote mobile robot's movement. A resistive touch screen was selected as the gesture sensor, then utilizing a programmed microcontroller to interpret them respectively.

Keywords: 2-Dimensional interface, finger gesture, mobile robot control, touch screen.

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Authors: Parvinder S. Sandhu, Hardeep Singh

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Automatic reusability appraisal could be helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable components from existing legacy systems; that can save cost of developing the software from scratch. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this paper, we have mentioned two-tier approach by studying the structural attributes as well as usability or relevancy of the component to a particular domain. Latent semantic analysis is used for the feature vector representation of various software domains. It exploits the fact that FeatureVector codes can be seen as documents containing terms -the idenifiers present in the components- and so text modeling methods that capture co-occurrence information in low-dimensional spaces can be used. Further, we devised Neuro- Fuzzy hybrid Inference System, which takes structural metric values as input and calculates the reusability of the software component. Decision tree algorithm is used to decide initial set of fuzzy rules for the Neuro-fuzzy system. The results obtained are convincing enough to propose the system for economical identification and retrieval of reusable software components.

Keywords: Clustering, ID3, LSA, Neuro-fuzzy System, SVD

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Authors: Katsuya Takasaki, Manabu Takao, Toshiaki Setoguchi

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The effect of a 3-dimensional (3D) blade on the turbine characteristics of Wells turbine for wave energy conversion has been investigated experimentally by model testing under steady flow conditions in this study, in order to improve the peak efficiency and stall characteristics. The aim of use of 3D blade is to prevent flow separation on the suction surface near the tip. The chord length is constant with radius and the blade profile changes gradually from the mean radius to tip. The proposed blade profiles in the study are NACA0015 from the hub to mean radius and NACA0025 at the tip. The performances of Wells turbine with 3D blades has been compared with those of the original Wells turbine, i.e., the turbine with 2-dimensional (2D) blades. As a result, it was concluded that although the peak efficiency of Wells turbine can be improved by the use of the proposed 3D blade, its blade does not overcome the weakness of stalling.

Keywords: Fluid machinery, ocean engineering, stall, wave energy conversion, Wells turbine.

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Authors: Ravihansa Rajapakse, Malshika Dias, Kanishka Weerasekara, Anuja Dharmaratne, Prasad Wimalaratne

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In this paper we discuss a set of guidelines which could be adapted when designing an audio user interface for the visually impaired. It is based on an audio environment that is focused on audio positioning. Unlike current applications which only interpret Graphical User Interface (GUI) for the visually impaired, this particular audio environment bypasses GUI to provide a direct auditory output. It presents the capability of two dimensional (2D) navigation on audio interfaces. This paper highlights the significance of a 2D audio environment with spatial information in the context of the visually impaired. A thorough usability study has been conducted to prove the applicability of proposed design guidelines for these auditory interfaces. While proving these guidelines, previously unearthed design aspects have been revealed in this study.

Keywords: Human Computer Interaction, Audio User Interfaces, 2D Audio Environment, Visually Impaired Users

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Authors: Fábio A. S. Mota, Mauro A. S. S. Ravagnani, E. P. Carvalho

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In the present paper the design of plate heat exchangers is formulated as an optimization problem considering two mathematical modelling. The number of plates is the objective function to be minimized, considering implicitly some parameters configuration. Screening is the optimization method used to solve the problem. Thermal and hydraulic constraints are verified, not viable solutions are discarded and the method searches for the convergence to the optimum, case it exists. A case study is presented to test the applicability of the developed algorithm. Results show coherency with the literature.

Keywords: Plate heat exchanger, optimization, modeling, simulation.

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Authors: Anna Avramenko, Heikki Haario

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This paper reports the development and application of a 2D1 depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. κ − ε and 2D LES turbulence models were consider in this article. 2D CFD2 simulations for one hill was done to check the depth-averaged model in practise.

Keywords: Depth-averaged equations, numerical modeling, CFD

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Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

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Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

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Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani

Abstract:

In this study, the absorbed dose of human organs after injection of ¹⁷⁷Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, ¹⁷⁷Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.

Keywords: Breast cancer, compartmental modeling, 177Lu, dosimetry.

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