Search results for: complex model

Authors: L. A. Bosnea, T. Moschakis, C. Biliaderis

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Two probiotic strains of Lactobacillus paracasei subsp. paracasei (E6) and Lactobacillus paraplantarum (B1), isolated from traditional Greek dairy products, were microencapsulated by complex coacervation using whey protein isolate (WPI, 3% w/v) and gum arabic (GA, 3% w/v) solutions mixed at different polymer ratio (1:1, 2:1 and 4:1). The effect of total biopolymer concentration on cell viability was assessed using WPI and GA solutions of 1, 3 and 6% w/v at a constant ratio of 2:1. Also, several parameters were examined for optimization of the microcapsule formation, such as inoculum concentration and the effect of ionic strength. The viability of the bacterial cells during heat treatment and under simulated gut conditions was also evaluated. Among the different WPI/GA weight ratios tested (1:1, 2:1, and 4:1), the highest survival rate was observed for the coacervate structures made with the ratio of 2:1. The protection efficiency at low pH values is influenced by both concentration and the ratio of the added biopolymers. Moreover, the inoculum concentration seems to affect the efficiency of microcapsules to entrap the bacterial cells since an optimum level was noted at less than 8 log cfu/ml. Generally, entrapment of lactobacilli in the complex coacervate structure enhanced the viability of the microorganisms when exposed to a low pH environment (pH 2.0). Both encapsulated strains retained high viability in simulated gastric juice (>73%), especially in comparison with non-encapsulated (free) cells (<19%). The encapsulated lactobacilli also exhibited enhanced viability after 10–30 min of heat treatment (65oC) as well as at different NaCl concentrations (pH 4.0). Overall, the results of this study suggest that complex coacervation with WPI/GA has a potential to deliver live probiotics in low pH food systems and fermented dairy products; the complexes can dissolve at pH 7.0 (gut environment), releasing the microbial cells.

Keywords: probiotic, complex coacervation, whey, encapsulation

Procedia PDF Downloads 297

Authors: Payam Haghparast, Mikhail V. Sorin, Hakim Nesreddine

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The complex oblique shock phenomenon can be simply assumed as a normal shock at the constant area section to simulate a sharp pressure increase and velocity decrease in 1-D thermodynamic models. The assumed normal shock location is one of the greatest sources of error in ejector thermodynamic models. Most researchers consider an arbitrary location without justifying it. Our study compares the effect of normal shock place on ejector dimensions in 1-D models. To this aim, two different ejector experimental test benches, a constant area-mixing ejector (CAM) and a constant pressure-mixing (CPM) are considered, with different known geometries, operating conditions and working fluids (R245fa, R141b). In the first step, in order to evaluate the real value of the efficiencies in the different ejector parts and critical back pressure, a CFD model was built and validated by experimental data for two types of ejectors. These reference data are then used as input to the 1D model to calculate the lengths and the diameters of the ejectors. Afterwards, the design output geometry calculated by the 1D model is compared directly with the corresponding experimental geometry. It was found that there is a good agreement between the ejector dimensions obtained by the 1D model, for both CAM and CPM, with experimental ejector data. Furthermore, it is shown that normal shock place affects only the constant area length as it is proven that the inlet normal shock assumption results in more accurate length. Taking into account previous 1D models, the results suggest the use of the assumed normal shock location at the inlet of the constant area duct to design the supersonic ejectors.

Keywords: 1D model, constant area-mixing, constant pressure-mixing, normal shock location, ejector dimensions

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Authors: Tarek Aboueldahab, Hanan Farag

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Cost minimization of Multiple Vehicle Routing Problem becomes a critical issue in the field of transportation because it is NP-hard optimization problem and the search space is complex. Many researches use the hybridization of artificial intelligence (AI) models to solve this problem; however, it can not guarantee to reach the best solution due to the difficulty of searching the whole search space. To overcome this problem, we introduce the hybrid model of Discrete Particle Swarm Optimization (DPSO) with a passive congregation which enable searching the whole search space to compromise between both local and global search. The practical experiment shows that our model obviously outperforms other hybrid models in cost minimization.

Keywords: cost minimization, multi-vehicle routing problem, passive congregation, discrete swarm, passive congregation

Procedia PDF Downloads 98

Authors: Jaouadi Imen, Ben Djemaa Raoudha, Ben Abdallah Hanene

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The access to relevant information that is adapted to users’ needs, preferences and environment is a challenge in many applications running. That causes an appearance of context-aware systems. To facilitate the development of this class of applications, it is necessary that these applications share a common context meta-model. In this article, we will present our context meta-model that is defined using the OMG Meta Object facility (MOF). This meta-model is based on the analysis and synthesis of context concepts proposed in literature.

Keywords: context, meta-model, MOF, awareness system

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Authors: Ayham Fattoum, Simos Chari, Duncan Shaw

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Volatile, uncertain, complex, and ambiguous (VUCA) conditions threaten systems viability with emerging and novel events requiring immediate and localized responses. Such responsiveness is only possible through devolved freedom and emancipated decision-making. The Viable System Model (VSM) recognizes the need and suggests maximizing autonomy to localize decision-making and minimize residual complexity. However, exercising delegated autonomy in VUCA requires confidence and knowledge to use intuition and guidance to maintain systemic coherence. This paper explores the role of intuition as an enabler of emancipated decision-making and autonomy under VUCA. Intuition allows decision-makers to use their knowledge and experience to respond rapidly to novel events. This paper offers three contributions to VSM. First, it designs a system model that illustrates the role of intuitive decision-making in managing complexity and maintaining viability. Second, it takes a black-box approach to theory development in VSM to model the role of autonomy and intuition. Third, the study uses a multi-stage discovery-oriented approach (DOA) to develop theory, with each stage combining literature, data analysis, and model/theory development and identifying further questions for the subsequent stage. We synthesize literature (e.g., VSM, complexity management) with seven months of field-based insights (interviews, workshops, and observation of a live disaster exercise) to develop a framework of intuitive complexity management framework and VSM models. The results have practical implications for enhancing the resilience of organizations and communities.

Keywords: Intuition, complexity management, decision-making, viable system model

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Authors: Mostafa Mjahed

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This paper concerns the control of a nonlinear system using two different methods, reference model and genetic algorithm. The quadcopter is a nonlinear unstable system, which is a part of aerial robots. It is constituted by four rotors placed at the end of a cross. The center of this cross is occupied by the control circuit. Its motions are governed by six degrees of freedom: three rotations around 3 axes (roll, pitch and yaw) and the three spatial translations. The control of such system is complex, because of nonlinearity of its dynamic representation and the number of parameters, which it involves. Numerous studies have been developed to model and stabilize such systems. The classical PID and LQ correction methods are widely used. If the latter represent the advantage to be simple because they are linear, they reveal the drawback to require the presence of a linear model to synthesize. It also implies the complexity of the established laws of command because the latter must be widened on all the domain of flight of these quadcopter. Note that, if the classical design methods are widely used to control aeronautical systems, the Artificial Intelligence methods as genetic algorithms technique receives little attention. In this paper, we suggest comparing two PID design methods. Firstly, the parameters of the PID are calculated according to the reference model. In a second phase, these parameters are established using genetic algorithms. By reference model, we mean that the corrected system behaves according to a reference system, imposed by some specifications: settling time, zero overshoot etc. Inspired from the natural evolution of Darwin's theory advocating the survival of the best, John Holland developed this evolutionary algorithm. Genetic algorithm (GA) possesses three basic operators: selection, crossover and mutation. We start iterations with an initial population. Each member of this population is evaluated through a fitness function. Our purpose is to correct the behavior of the quadcopter around three axes (roll, pitch and yaw) with 3 PD controllers. For the altitude, we adopt a PID controller.

Keywords: quadcopter, genetic algorithm, PID, fitness, model, control, nonlinear system

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Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

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The paper presents logical-probabilistic methods, models and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of weights of elements. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research and designing of optimal structure systems are carried out.

Keywords: Complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability, weight of element

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Authors: Aleš Florian, Lenka Ševelová

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Complex sensitivity analysis of stresses in a concrete slab of the real type of rigid pavement made from recycled materials is performed. The computational model of the pavement is designed as a spatial (3D) model, is based on a nonlinear variant of the finite element method that respects the structural nonlinearity, enables to model different arrangements of joints, and the entire model can be loaded by the thermal load. Interaction of adjacent slabs in joints and contact of the slab and the subsequent layer are modeled with the help of special contact elements. Four concrete slabs separated by transverse and longitudinal joints and the additional structural layers and soil to the depth of about 3m are modeled. The thickness of individual layers, physical and mechanical properties of materials, characteristics of joints, and the temperature of the upper and lower surface of slabs are supposed to be random variables. The modern simulation technique Updated Latin Hypercube Sampling with 20 simulations is used. For sensitivity analysis the sensitivity coefficient based on the Spearman rank correlation coefficient is utilized. As a result, the estimates of influence of random variability of individual input variables on the random variability of principal stresses s1 and s3 in 53 points on the upper and lower surface of the concrete slabs are obtained.

Keywords: concrete, FEM, pavement, sensitivity, simulation

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Authors: William Albeiro Alvarez, Gloria Patricia Jaramillo, Ivan Reinaldo Sarmiento

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Understanding the behavior of individuals and the different human factors that influence the choice when faced with a complex system such as transportation is one of the most complicated aspects of measuring in the components that constitute the modeling of route choice due to that various behaviors and driving mode directly or indirectly affect the choice. During the last two decades, with the development of information and communications technologies, new data collection techniques have emerged such as GPS, geolocation with mobile phones, apps for choosing the route between origin and destination, individual service transport applications among others, where an interest has been generated to improve discrete choice models when considering the incorporation of these developments as well as psychological factors that affect decision making. This paper implements a discrete choice model that proposes and estimates a hybrid model that integrates route choice models and latent variables based on the observation on the route of a sample of public taxi drivers from the city of Medellín, Colombia in relation to its behavior, personality, socioeconomic characteristics, and driving mode. The set of choice options includes the routes generated by the individual service transport applications versus the driver's choice. The hybrid model consists of measurement equations that relate latent variables with measurement indicators and utilities with choice indicators along with structural equations that link the observable characteristics of drivers with latent variables and explanatory variables with utilities.

Keywords: behavior choice model, human factors, hybrid model, real time data

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Amr Abdel Azim Ali, G. A. Elsheikh, Moutaz Hegazy

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This paper presents verification of a modeling and simulation for a Spacecraft (SC) attitude and orbit control system. Detailed formulation of coupled SC orbital and attitude equations of motion is performed in order to achieve accepted accuracy to meet the requirements of multitargets tracking and orbit correction complex modes. Correction of the target parameter based on the estimated state vector during shooting time to enhance pointing accuracy is considered. Time-optimal nonlinear feedback control technique was used in order to take full advantage of the maximum torques that the controller can deliver. This simulation provides options for visualizing SC trajectory and attitude in a 3D environment by including an interface with V-Realm Builder and VR Sink in Simulink/MATLAB. Verification data confirms the simulation results, ensuring that the model and the proposed control law can be used successfully for large and fast tracking and is robust enough to keep the pointing accuracy within the desired limits with considerable uncertainty in inertia and control torque.

Keywords: attitude and orbit control, time-optimal nonlinear feedback control, modeling and simulation, pointing accuracy, maximum torques

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Authors: K. Sekulová, M. Šimon

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This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Keywords: ergonomics, musculoskeletal disorders, occupational diseases, risk factors

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Authors: Anthony Usoro

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In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

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Authors: Andrzej Kesiak

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Contemporary theology is often accused of answering questions that nobody is asking, and of employing hermetic language that has lost its communication capacity. There is also a question that theology is asking itself: how theological discourse can still be influential on other disciplines and, how to overcome the separation of theology and belief. Undoubtedly, in the wider spectrum, the theological discourse has been and will be needed. The difficulty is how to find the right model of it, the model that would help theology to enter in dialogue with culture, art, science, and politics. Presumably, there is no only one such model, theology constantly needs to seek such models, and this is probably a never-ending journey; in other words, theology should adopt a profile of ‘a restless being’ if it wants to remain influential. Music, on the other hand, has always been very close to theology; in fact, a huge part of classical music is either sacred or religious. Many composers sought inspiration in religion, liturgy, religious painting and sacred texts. This paper will argue that despite all that it seems that a proper and factual dialogue is still in a starting phase. Such a thing as a reciprocal relationship between theology and music definitely exists, but it has not yet been theoretically developed enough. Correlation between musical and theological disciplines constitutes a very broad and complex discourse. Therefore this study would rather narrow the subject and put it in a specific context: Theology and Music in the XXI. Century. This paper is a text-based study; therefore it will be based on textual-analysis with elements of the text hermeneutics.

Keywords: music, theology, reciprocal relationship between theology and music, XXI Century

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Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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Authors: Radim Sip, Denisa Denglerova

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It’s impossible to capture complex phenomena, such as inclusion, with reductionism. The most common form of reductionism is the objectivist approach, where processes and relationships are reduced to entities and clearly outlined phases, with a consequent search for relationships between them. Constructivism as a paradigm and situational analysis as a methodological research portfolio represent a way to avoid the dominant objectivist approach. They work with a situation, i.e. with the essential blending of actors and their environment. Primary transactions are taking place between actors and their surroundings. Researchers create constructs based on their need to solve a problem. Concepts therefore do not describe reality, but rather a complex of real needs in relation to the available options how such needs can be met. For examination of a complex problem, corresponding methodological tools and overall design of the research are necessary. Using an original research on inclusion in the Czech Republic as an example, this contribution demonstrates that inclusion is not a substance easily described, but rather a relationship field changing its forms in response to its actors’ behaviour and current circumstances. Inclusion consists of dynamic relationship between an ideal, real circumstances and ways to achieve such ideal under the given circumstances. Such achievement has many shapes and thus cannot be captured by description of objects. It can be expressed in relationships in the situation defined by time and space. Situational analysis offers tools to examine such phenomena. It understands a situation as a complex of dynamically changing aspects and prefers relationships and positions in the given situation over a clear and final definition of actors, entities, etc. Situational analysis assumes creation of constructs as a tool for solving a problem at hand. It emphasizes the meanings that arise in the process of coordinating human actions, and the discourses through which these meanings are negotiated. Finally, it offers “cartographic tools” (situational maps, socials worlds / arenas maps, positional maps) that are able to capture the complexity in other than linear-analytical ways. This approach allows for inclusion to be described as a complex of phenomena taking place with a certain historical preference, a complex that can be overlooked if analyzed with a more traditional approach.

Keywords: constructivism, situational analysis, objective realism, reductionism, inclusion

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Authors: Subhash Chandra Sharma, Mohammad Soleimani

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Selection of the correct lubricant for the top of rail application is a complex process. In this paper, the selection of the proper lubricant for a Top-Of-Rail (TOR) lubrication system based on graph theory and matrix approach has been developed. Attributes influencing the selection process and their influence on each other has been represented through a digraph and an equivalent matrix. A matrix function which is called the Permanent Function is derived. By substituting the level of inherent contribution of the influencing parameters and their influence on each other qualitatively, a criterion called Suitability Index is derived. Based on these indices, lubricants can be ranked for their suitability. The proposed model can be useful for maintenance engineers in selecting the best lubricant for a TOR application. The proposed methodology is illustrated step–by-step through an example.

Keywords: lubricant selection, top of rail lubrication, graph-theory, Ranking of lubricants

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Authors: Shank Kulkarni, Alireza Tabarraei

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The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.

Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test

Procedia PDF Downloads 243

Authors: Thiago Victor Cordeiro Marcos, Joao Felipe de Araujo Martos, Ronaldo de Lima Cardoso, David Romanelli Pinto, Paulo Gilberto de Paula Toro, Israel da Silveira Rego, Antonio Carlos de Oliveira

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Currently, the use of 3D rapid prototyping, also known as 3D printing, has been investigated by some universities around the world as an innovative technique, fast, flexible and cheap for a direct plastic models manufacturing that are lighter and with complex geometries to be tested for hypersonic shock tunnel. Initially, the purpose is integrated prototyped parts with metal models that actually are manufactured through of the conventional machining and hereafter replace them with completely prototyped models. The mechanical design models to be tested in hypersonic shock tunnel are based on conventional manufacturing processes, therefore are limited forms and standard geometries. The use of 3D rapid prototyping offers a range of options that enables geometries innovation and ways to be used for the design new models. The conception and project of a prototyped model for hypersonic shock tunnel should be rethought and adapted when comparing the conventional manufacturing processes, in order to fully exploit the creativity and flexibility that are allowed by the 3D prototyping process. The objective of this paper is to compare the conception and project of a 3D rapid prototyping model and a conventional machining model, while showing the advantages and disadvantages of each process and the benefits that 3D prototyping can bring to the manufacture of models to be tested in hypersonic shock tunnel.

Keywords: 3D printing, 3D prototyping, experimental research, hypersonic shock tunnel

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Authors: Hussein Altartouri

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In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.

Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot

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Authors: Yulii D. Shikhmurzaev

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The modelling of the non-isothermal free-surface flows coupled with the solidification process has become the topic of intensive research with the advent of additive manufacturing, where complex 3-dimensional structures are produced by successive deposition and solidification of microscopic droplets of different materials. The issue is that both the spreading of liquids over solids and the propagation of the solidification front into the fluid and along the solid substrate pose fundamental difficulties for their mathematical modelling. The first of these processes, known as ‘dynamic wetting’, leads to the well-known ‘moving contact-line problem’ where, as shown recently both experimentally and theoretically, the contact angle formed by the free surfac with the solid substrate is not a function of the contact-line speed but is rather a functional of the flow field. The modelling of the propagating solidification front requires generalization of the classical Stefan problem, which would be able to describe the onset of the process and the non-equilibrium regime of solidification. Furthermore, given that both dynamic wetting and solification occur concurrently and interactively, they should be described within the same conceptual framework. The present work addresses this formidable problem and presents a mathematical model capable of describing the key element of additive manufacturing in a self-consistent and singularity-free way. The model is illustrated simple examples highlighting its main features. The main idea of the work is that both dynamic wetting and solidification, as well as some other fluid flows, are particular cases in a general class of flows where interfaces form and/or disappear. This conceptual framework allows one to derive a mathematical model from first principles using the methods of irreversible thermodynamics. Crucially, the interfaces are not considered as zero-mass entities introduced using Gibbsian ‘dividing surface’ but the 2-dimensional surface phases produced by the continuum limit in which the thickness of what physically is an interfacial layer vanishes, and its properties are characterized by ‘surface’ parameters (surface tension, surface density, etc). This approach allows for the mass exchange between the surface and bulk phases, which is the essence of the interface formation. As shown numerically, the onset of solidification is preceded by the pure interface formation stage, whilst the Stefan regime is the final stage where the temperature at the solidification front asymptotically approaches the solidification temperature. The developed model can also be applied to the flow with the substrate melting as well as a complex flow where both types of phase transition take place.

Keywords: dynamic wetting, interface formation, phase transition, solidification

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Authors: Tewele Gebretsadkan Haile

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Mountain terrains are essential to regional water resources by regulating hydrological processes that use downstream water supplies. Nevertheless, limited observed earth data in complex topography poses challenges for water resources regulation. That's why satellite product is implemented in this study. This study evaluates hydrological processes on mountain catchment of Gumera, Ethiopia using HBV-light model with satellite precipitation products (CHIRPS) for the temporal scale of 1996 to 2010 and area coverage of 1289 km2. The catchment is characterized by cultivation dominant and elevation ranges from 1788 to 3606 m above sea level. Three meteorological stations have been used for downscaling of the satellite data and one stream flow for calibration and validation. The result shows total annual water balance showed that precipitation 1410 mm, simulated 828 mm surface runoff compared to 1042 mm observed stream flow with actual evapotranspiration estimate 586mm and 1495mm potential evapotranspiration. The temperature range is 9°C in winter to 21°C. The catchment contributes 74% as quack runoff to the total runoff and 26% as lower groundwater storage, which sustains stream flow during low periods. The model uncertainty was measured using different metrics such as coefficient of determination, model efficiency, efficiency for log(Q) and flow weighted efficiency 0.76, 0.74, 0.66 and 0.70 respectively. The research result highlights that HBV model captures the mountain hydrology simulation and the result indicates quack runoff due to the traditional agricultural system, slope factor of the topography and adaptation measure for water resource management is recommended.

Keywords: mountain hydrology, CHIRPS, Gumera, HBV model

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Authors: Tewele Gebretsadkan Haile

Abstract:

Mountain terrains are essential to regional water resources by regulating hydrological processes that use downstream water supplies. Nevertheless, limited observed earth data in complex topography poses challenges for water resources regulation. That's why satellite product is implemented in this study. This study evaluates hydrological processes on mountain catchment of Gumera, Ethiopia using HBV-light model with satellite precipitation products (CHIRPS) for the temporal scale of 1996 to 2010 and area coverage of 1289 km2. The catchment is characterized by cultivation dominant and elevation ranges from 1788 to 3606 m above sea level. Three meteorological stations have been used for downscaling of the satellite data and one stream flow for calibration and validation. The result shows total annual water balance showed that precipitation 1410 mm, simulated 828 mm surface runoff compared to 1042 mm observed stream flow with actual evapotranspiration estimate 586mm and 1495mm potential evapotranspiration. The temperature range is 9°C in winter to 21°C. The catchment contributes 74% as quack runoff to the total runoff and 26% as lower groundwater storage, which sustains stream flow during low periods. The model uncertainty was measured using different metrics such as coefficient of determination, model efficiency, efficiency for log(Q) and flow weighted efficiency 0.76, 0.74, 0.66 and 0.70 respectively. The research result highlights that HBV model captures the mountain hydrology simulation and the result indicates quack runoff due to the traditional agricultural system, slope factor of the topography and adaptation measure for water resource management is recommended.

Keywords: mountain hydrology, CHIRPS, HBV model, Gumera

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Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: bounding surface, consistency theory, constitutive model, viscosity

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Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

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The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

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Authors: Mohamed Boullouz, Mohamed Louay Metougui

Abstract:

Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

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Authors: Janneth Gonzalez, Andrés Pinzon Velasco, Maria Angarita

Abstract:

Astrocytes play an important role in various processes in the brain, including pathological conditions such as neurodegenerative diseases. Recent studies have shown that the increase in saturated fatty acids such as palmitic acid (PA) triggers pro-inflammatorypathways in the brain. The use of synthetic neurosteroids such as tibolone has demonstrated neuro-protective mechanisms. However, broad studies with a systemic point of view on the neurodegenerative role of PA and the neuro-protective mechanisms of tibolone are lacking. In this study, we performed the integration of multi-omic data (transcriptome and proteome) into a human astrocyte genomic scale metabolic model to study the astrocytic response during palmitate treatment. We evaluated metabolic fluxes in three scenarios (healthy, induced inflammation by PA, and tibolone treatment under PA inflammation). We also applied a control theory approach to identify those reactions that exert more control in the astrocytic system. Our results suggest that PA generates a modulation of central and secondary metabolism, showing a switch in energy source use through inhibition of folate cycle and fatty acid β‐oxidation and upregulation of ketone bodies formation. We found 25 metabolic switches under PA‐mediated cellular regulation, 9 of which were critical only in the inflammatory scenario but not in the protective tibolone one. Within these reactions, inhibitory, total, and directional coupling profiles were key findings, playing a fundamental role in the (de)regulation of metabolic pathways that may increase neurotoxicity and represent potential treatment targets. Finally, the overall framework of our approach facilitates the understanding of complex metabolic regulation, and it can be used for in silico exploration of the mechanisms of astrocytic cell regulation, directing a more complex future experimental work in neurodegenerative diseases.

Keywords: astrocytes, data integration, palmitic acid, computational model, multi-omics

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Authors: Justin Nwabanne, Sam Omenyi, Jeremiah Chukwuneke

Abstract:

This work presents structural nonlinear static analysis of a horizontal taut cable using Finite Element Analysis (FEA) method. The FEA was performed analytically to determine the tensions at each nodal point and subsequently, performed based on finite element displacement method computationally using the FEA software, ANSYS 14.0 to determine their behaviour under the influence of aerodynamic forces imposed on the cable. The convergence procedure is adapted into the method to prevent excessive displacements through the computations. The work compared the two FEA cases by examining the effectiveness of the analytical model in describing the response with few degrees of freedom and the ability of the nonlinear finite element procedure adopted to capture the complex features of cable dynamics with reference to the aerodynamic external influence. Results obtained from this work explain that the analytic FEM results without aerodynamic influence show a parabolic response with an optimum deflection at nodal points 12 and 13 with the cable weight at nodes 12 and 13 having the value -1.002936N while for the cable tension shows an optimum deflection value for nodes 12 and 13 at -189396.97kg/km. The maximum displacement for the cable system was obtained from ANSYS 14.0 as 4483.83 mm for X, Y and Z components of displacements at node number 2 while the maximum displacement obtained is 4218.75mm for all the directional components. The dynamic behaviour of a taut cable investigated has application in a typical power transmission line. Aerodynamic influences on the cables were considered using FEA approach by employing ANSYS 14.0 showed a complex modal behaviour as expected.

Keywords: aerodynamics, cable tension and weight, finite element analysis, nodal, non-linear model, optimum deflection, suspended cable, transmission line

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Authors: P. D. Pastuszak

Abstract:

The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: active thermography, composite, curved structures, defects

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Authors: A. Mudau, T. R. Stacey, R. A. Govender

Abstract:

This paper reports for the first time the findings on the dynamic compressive strength data of Bushveld Complex brittle rock materials. These rocks were subjected to both quasi-static and impact loading tests to help understand their behaviour both under quasi-static and dynamic loading conditions. Unlike quasi-static tests, characterization of dynamic behaviour of materials is challenging, in particularly brittle rock materials. The split Hopkinson pressure bar (SHPB) results reported for anorthosite and norite showed relatively low values for dynamic compressive strength compared to the quasi-static uniaxial compressive strength data. It was noticed that the dynamic stress conditions were not fully attained during testing, as well as constant strain rate.

Keywords: Bushveld Complex, dynamic comperession, rock brittleness, stress equilibrium

Procedia PDF Downloads 498