Search results for: MATLAB/Simulink
55 Dogs Chest Homogeneous Phantom for Image Optimization
Authors: Maris Eugênia Dela Rosa, Ana Luiza Menegatti Pavan, Marcela De Oliveira, Diana Rodrigues De Pina, Luis Carlos Vulcano
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In medical veterinary as well as in human medicine, radiological study is essential for a safe diagnosis in clinical practice. Thus, the quality of radiographic image is crucial. In last year’s there has been an increasing substitution of image acquisition screen-film systems for computed radiology equipment (CR) without technical charts adequacy. Furthermore, to carry out a radiographic examination in veterinary patient is required human assistance for restraint this, which can compromise image quality by generating dose increasing to the animal, for Occupationally Exposed and also the increased cost to the institution. The image optimization procedure and construction of radiographic techniques are performed with the use of homogeneous phantoms. In this study, we sought to develop a homogeneous phantom of canine chest to be applied to the optimization of these images for the CR system. In carrying out the simulator was created a database with retrospectives chest images of computed tomography (CT) of the Veterinary Hospital of the Faculty of Veterinary Medicine and Animal Science - UNESP (FMVZ / Botucatu). Images were divided into four groups according to the animal weight employing classification by sizes proposed by Hoskins & Goldston. The thickness of biological tissues were quantified in a 80 animals, separated in groups of 20 animals according to their weights: (S) Small - equal to or less than 9.0 kg, (M) Medium - between 9.0 and 23.0 kg, (L) Large – between 23.1 and 40.0kg and (G) Giant – over 40.1 kg. Mean weight for group (S) was 6.5±2.0 kg, (M) 15.0±5.0 kg, (L) 32.0±5.5 kg and (G) 50.0 ±12.0 kg. An algorithm was developed in Matlab in order to classify and quantify biological tissues present in CT images and convert them in simulator materials. To classify tissues presents, the membership functions were created from the retrospective CT scans according to the type of tissue (adipose, muscle, bone trabecular or cortical and lung tissue). After conversion of the biologic tissue thickness in equivalent material thicknesses (acrylic simulating soft tissues, bone tissues simulated by aluminum and air to the lung) were obtained four different homogeneous phantoms, with (S) 5 cm of acrylic, 0,14 cm of aluminum and 1,8 cm of air; (M) 8,7 cm of acrylic, 0,2 cm of aluminum and 2,4 cm of air; (L) 10,6 cm of acrylic, 0,27 cm of aluminum and 3,1 cm of air and (G) 14,8 cm of acrylic, 0,33 cm of aluminum and 3,8 cm of air. The developed canine homogeneous phantom is a practical tool, which will be employed in future, works to optimize veterinary X-ray procedures.Keywords: radiation protection, phantom, veterinary radiology, computed radiography
Procedia PDF Downloads 41054 Modeling of the Fermentation Process of Enzymatically Extracted Annona muricata L. Juice
Authors: Calister Wingang Makebe, Wilson Agwanande Ambindei, Zangue Steve Carly Desobgo, Abraham Billu, Emmanuel Jong Nso, P. Nisha
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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1, as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics
Procedia PDF Downloads 5753 Mathematical Modelling of Biogas Dehumidification by Using of Counterflow Heat Exchanger
Authors: Staņislavs Gendelis, Andris Jakovičs, Jānis Ratnieks, Aigars Laizāns, Dāvids Vardanjans
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Dehumidification of biogas at the biomass plants is very important to provide the energy efficient burning of biomethane at the outlet. A few methods are widely used to reduce the water content in biogas, e.g. chiller/heat exchanger based cooling, usage of different adsorbents like PSA, or the combination of such approaches. A quite different method of biogas dehumidification is offered and analyzed in this paper. The main idea is to direct the flow of biogas from the plant around it downwards; thus, creating additional insulation layer. As the temperature in gas shell layer around the plant will decrease from ~ 38°C to 20°C in the summer or even to 0°C in the winter, condensation of water vapor occurs. The water from the bottom of the gas shell can be collected and drain away. In addition, another upward shell layer is created after the condensate drainage place on the outer side to further reducing heat losses. Thus, counterflow biogas heat exchanger is created around the biogas plant. This research work deals with the numerical modelling of biogas flow, taking into account heat exchange and condensation on cold surfaces. Different kinds of boundary conditions (air and ground temperatures in summer/winter) and various physical properties of constructions (insulation between layers, wall thickness) are included in the model to make it more general and useful for different biogas flow conditions. The complexity of this problem is fact, that the temperatures in both channels are conjugated in case of low thermal resistance between layers. MATLAB programming language is used for multiphysical model development, numerical calculations and result visualization. Experimental installation of a biogas plant’s vertical wall with an additional 2 layers of polycarbonate sheets with the controlled gas flow was set up to verify the modelling results. Gas flow at inlet/outlet, temperatures between the layers and humidity were controlled and measured during a number of experiments. Good correlation with modelling results for vertical wall section allows using of developed numerical model for an estimation of parameters for the whole biogas dehumidification system. Numerical modelling of biogas counterflow heat exchanger system placed on the plant’s wall for various cases allows optimizing of thickness for gas layers and insulation layer to ensure necessary dehumidification of the gas under different climatic conditions. Modelling of system’s defined configuration with known conditions helps to predict the temperature and humidity content of the biogas at the outlet.Keywords: biogas dehumidification, numerical modelling, condensation, biogas plant experimental model
Procedia PDF Downloads 54152 Comparing Xbar Charts: Conventional versus Reweighted Robust Estimation Methods for Univariate Data Sets
Authors: Ece Cigdem Mutlu, Burak Alakent
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Maintaining the quality of manufactured products at a desired level depends on the stability of process dispersion and location parameters and detection of perturbations in these parameters as promptly as possible. Shewhart control chart is the most widely used technique in statistical process monitoring to monitor the quality of products and control process mean and variability. In the application of Xbar control charts, sample standard deviation and sample mean are known to be the most efficient conventional estimators in determining process dispersion and location parameters, respectively, based on the assumption of independent and normally distributed datasets. On the other hand, there is no guarantee that the real-world data would be normally distributed. In the cases of estimated process parameters from Phase I data clouded with outliers, efficiency of traditional estimators is significantly reduced, and performance of Xbar charts are undesirably low, e.g. occasional outliers in the rational subgroups in Phase I data set may considerably affect the sample mean and standard deviation, resulting a serious delay in detection of inferior products in Phase II. For more efficient application of control charts, it is required to use robust estimators against contaminations, which may exist in Phase I. In the current study, we present a simple approach to construct robust Xbar control charts using average distance to the median, Qn-estimator of scale, M-estimator of scale with logistic psi-function in the estimation of process dispersion parameter, and Harrell-Davis qth quantile estimator, Hodge-Lehmann estimator and M-estimator of location with Huber psi-function and logistic psi-function in the estimation of process location parameter. Phase I efficiency of proposed estimators and Phase II performance of Xbar charts constructed from these estimators are compared with the conventional mean and standard deviation statistics both under normality and against diffuse-localized and symmetric-asymmetric contaminations using 50,000 Monte Carlo simulations on MATLAB. Consequently, it is found that robust estimators yield parameter estimates with higher efficiency against all types of contaminations, and Xbar charts constructed using robust estimators have higher power in detecting disturbances, compared to conventional methods. Additionally, utilizing individuals charts to screen outlier subgroups and employing different combination of dispersion and location estimators on subgroups and individual observations are found to improve the performance of Xbar charts.Keywords: average run length, M-estimators, quality control, robust estimators
Procedia PDF Downloads 18051 Frequency Response of Complex Systems with Localized Nonlinearities
Authors: E. Menga, S. Hernandez
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Finite Element Models (FEMs) are widely used in order to study and predict the dynamic properties of structures and usually, the prediction can be obtained with much more accuracy in the case of a single component than in the case of assemblies. Especially for structural dynamics studies, in the low and middle frequency range, most complex FEMs can be seen as assemblies made by linear components joined together at interfaces. From a modelling and computational point of view, these types of joints can be seen as localized sources of stiffness and damping and can be modelled as lumped spring/damper elements, most of time, characterized by nonlinear constitutive laws. On the other side, most of FE programs are able to run nonlinear analysis in time-domain. They treat the whole structure as nonlinear, even if there is one nonlinear degree of freedom (DOF) out of thousands of linear ones, making the analysis unnecessarily expensive from a computational point of view. In this work, a methodology in order to obtain the nonlinear frequency response of structures, whose nonlinearities can be considered as localized sources, is presented. The work extends the well-known Structural Dynamic Modification Method (SDMM) to a nonlinear set of modifications, and allows getting the Nonlinear Frequency Response Functions (NLFRFs), through an ‘updating’ process of the Linear Frequency Response Functions (LFRFs). A brief summary of the analytical concepts is given, starting from the linear formulation and understanding what the implications of the nonlinear one, are. The response of the system is formulated in both: time and frequency domain. First the Modal Database is extracted and the linear response is calculated. Secondly the nonlinear response is obtained thru the NL SDMM, by updating the underlying linear behavior of the system. The methodology, implemented in MATLAB, has been successfully applied to estimate the nonlinear frequency response of two systems. The first one is a two DOFs spring-mass-damper system, and the second example takes into account a full aircraft FE Model. In spite of the different levels of complexity, both examples show the reliability and effectiveness of the method. The results highlight a feasible and robust procedure, which allows a quick estimation of the effect of localized nonlinearities on the dynamic behavior. The method is particularly powerful when most of the FE Model can be considered as acting linearly and the nonlinear behavior is restricted to few degrees of freedom. The procedure is very attractive from a computational point of view because the FEM needs to be run just once, which allows faster nonlinear sensitivity analysis and easier implementation of optimization procedures for the calibration of nonlinear models.Keywords: frequency response, nonlinear dynamics, structural dynamic modification, softening effect, rubber
Procedia PDF Downloads 26150 Magnetic Navigation in Underwater Networks
Authors: Kumar Divyendra
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Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.Keywords: clustering, deep learning, network backbone, parallel computing
Procedia PDF Downloads 8749 Environmental Benefits of Corn Cob Ash in Lateritic Soil Cement Stabilization for Road Works in a Sub-Tropical Region
Authors: Ahmed O. Apampa, Yinusa A. Jimoh
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The potential economic viability and environmental benefits of using a biomass waste, such as corn cob ash (CCA) as pozzolan in stabilizing soils for road pavement construction in a sub-tropical region was investigated. Corn cob was obtained from Maya in South West Nigeria and processed to ash of characteristics similar to Class C Fly Ash pozzolan as specified in ASTM C618-12. This was then blended with ordinary Portland cement in the CCA:OPC ratios of 1:1, 1:2 and 2:1. Each of these blends was then mixed with lateritic soil of ASHTO classification A-2-6(3) in varying percentages from 0 – 7.5% at 1.5% intervals. The soil-CCA-Cement mixtures were thereafter tested for geotechnical index properties including the BS Proctor Compaction, California Bearing Ratio (CBR) and the Unconfined Compression Strength Test. The tests were repeated for soil-cement mix without any CCA blending. The cost of the binder inputs and optimal blends of CCA:OPC in the stabilized soil were thereafter analyzed by developing algorithms that relate the experimental data on strength parameters (Unconfined Compression Strength, UCS and California Bearing Ratio, CBR) with the bivariate independent variables CCA and OPC content, using Matlab R2011b. An optimization problem was then set up minimizing the cost of chemical stabilization of laterite with CCA and OPC, subject to the constraints of minimum strength specifications. The Evolutionary Engine as well as the Generalized Reduced Gradient option of the Solver of MS Excel 2010 were used separately on the cells to obtain the optimal blend of CCA:OPC. The optimal blend attaining the required strength of 1800 kN/m2 was determined for the 1:2 CCA:OPC as 5.4% mix (OPC content 3.6%) compared with 4.2% for the OPC only option; and as 6.2% mix for the 1:1 blend (OPC content 3%). The 2:1 blend did not attain the required strength, though over a 100% gain in UCS value was obtained over the control sample with 0% binder. Upon the fact that 0.97 tonne of CO2 is released for every tonne of cement used (OEE, 2001), the reduced OPC requirement to attain the same result indicates the possibility of reducing the net CO2 contribution of the construction industry to the environment ranging from 14 – 28.5% if CCA:OPC blends are widely used in soil stabilization, going by the results of this study. The paper concludes by recommending that Nigeria and other developing countries in the sub-tropics with abundant stock of biomass waste should look in the direction of intensifying the use of biomass waste as fuel and the derived ash for the production of pozzolans for road-works, thereby reducing overall green house gas emissions and in compliance with the objectives of the United Nations Framework on Climate Change.Keywords: corn cob ash, biomass waste, lateritic soil, unconfined compression strength, CO2 emission
Procedia PDF Downloads 36848 Elasto-Plastic Analysis of Structures Using Adaptive Gaussian Springs Based Applied Element Method
Authors: Mai Abdul Latif, Yuntian Feng
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Applied Element Method (AEM) is a method that was developed to aid in the analysis of the collapse of structures. Current available methods cannot deal with structural collapse accurately; however, AEM can simulate the behavior of a structure from an initial state of no loading until collapse of the structure. The elements in AEM are connected with sets of normal and shear springs along the edges of the elements, that represent the stresses and strains of the element in that region. The elements are rigid, and the material properties are introduced through the spring stiffness. Nonlinear dynamic analysis has been widely modelled using the finite element method for analysis of progressive collapse of structures; however, difficulties in the analysis were found at the presence of excessively deformed elements with cracking or crushing, as well as having a high computational cost, and difficulties on choosing the appropriate material models for analysis. The Applied Element method is developed and coded to significantly improve the accuracy and also reduce the computational costs of the method. The scheme works for both linear elastic, and nonlinear cases, including elasto-plastic materials. This paper will focus on elastic and elasto-plastic material behaviour, where the number of springs required for an accurate analysis is tested. A steel cantilever beam is used as the structural element for the analysis. The first modification of the method is based on the Gaussian Quadrature to distribute the springs. Usually, the springs are equally distributed along the face of the element, but it was found that using Gaussian springs, only up to 2 springs were required for perfectly elastic cases, while with equal springs at least 5 springs were required. The method runs on a Newton-Raphson iteration scheme, and quadratic convergence was obtained. The second modification is based on adapting the number of springs required depending on the elasticity of the material. After the first Newton Raphson iteration, Von Mises stress conditions were used to calculate the stresses in the springs, and the springs are classified as elastic or plastic. Then transition springs, springs located exactly between the elastic and plastic region, are interpolated between regions to strictly identify the elastic and plastic regions in the cross section. Since a rectangular cross-section was analyzed, there were two plastic regions (top and bottom), and one elastic region (middle). The results of the present study show that elasto-plastic cases require only 2 springs for the elastic region, and 2 springs for the plastic region. This showed to improve the computational cost, reducing the minimum number of springs in elasto-plastic cases to only 6 springs. All the work is done using MATLAB and the results will be compared to models of structural elements using the finite element method in ANSYS.Keywords: applied element method, elasto-plastic, Gaussian springs, nonlinear
Procedia PDF Downloads 21747 Theta-Phase Gamma-Amplitude Coupling as a Neurophysiological Marker in Neuroleptic-Naive Schizophrenia
Authors: Jun Won Kim
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Objective: Theta-phase gamma-amplitude coupling (TGC) was used as a novel evidence-based tool to reflect the dysfunctional cortico-thalamic interaction in patients with schizophrenia. However, to our best knowledge, no studies have reported the diagnostic utility of the TGC in the resting-state electroencephalographic (EEG) of neuroleptic-naive patients with schizophrenia compared to healthy controls. Thus, the purpose of this EEG study was to understand the underlying mechanisms in patients with schizophrenia by comparing the TGC at rest between two groups and to evaluate the diagnostic utility of TGC. Method: The subjects included 90 patients with schizophrenia and 90 healthy controls. All patients were diagnosed with schizophrenia according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) by two independent psychiatrists using semi-structured clinical interviews. Because patients were either drug-naïve (first episode) or had not been taking psychoactive drugs for one month before the study, we could exclude the influence of medications. Five frequency bands were defined for spectral analyses: delta (1–4 Hz), theta (4–8 Hz), slow alpha (8–10 Hz), fast alpha (10–13.5 Hz), beta (13.5–30 Hz), and gamma (30-80 Hz). The spectral power of the EEG data was calculated with fast Fourier Transformation using the 'spectrogram.m' function of the signal processing toolbox in Matlab. An analysis of covariance (ANCOVA) was performed to compare the TGC results between the groups, which were adjusted using a Bonferroni correction (P < 0.05/19 = 0.0026). Receiver operator characteristic (ROC) analysis was conducted to examine the discriminating ability of the TGC data for schizophrenia diagnosis. Results: The patients with schizophrenia showed a significant increase in the resting-state TGC at all electrodes. The delta, theta, slow alpha, fast alpha, and beta powers showed low accuracies of 62.2%, 58.4%, 56.9%, 60.9%, and 59.0%, respectively, in discriminating the patients with schizophrenia from the healthy controls. The ROC analysis performed on the TGC data generated the most accurate result among the EEG measures, displaying an overall classification accuracy of 92.5%. Conclusion: As TGC includes phase, which contains information about neuronal interactions from the EEG recording, TGC is expected to be useful for understanding the mechanisms the dysfunctional cortico-thalamic interaction in patients with schizophrenia. The resting-state TGC value was increased in the patients with schizophrenia compared to that in the healthy controls and had a higher discriminating ability than the other parameters. These findings may be related to the compensatory hyper-arousal patterns of the dysfunctional default-mode network (DMN) in schizophrenia. Further research exploring the association between TGC and medical or psychiatric conditions that may confound EEG signals will help clarify the potential utility of TGC.Keywords: quantitative electroencephalography (QEEG), theta-phase gamma-amplitude coupling (TGC), schizophrenia, diagnostic utility
Procedia PDF Downloads 13046 Effectiveness Factor for Non-Catalytic Gas-Solid Pyrolysis Reaction for Biomass Pellet Under Power Law Kinetics
Authors: Haseen Siddiqui, Sanjay M. Mahajani
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Various important reactions in chemical and metallurgical industries fall in the category of gas-solid reactions. These reactions can be categorized as catalytic and non-catalytic gas-solid reactions. In gas-solid reaction systems, heat and mass transfer limitations put an appreciable influence on the rate of the reaction. The consequences can be unavoidable for overlooking such effects while collecting the reaction rate data for the design of the reactor. Pyrolysis reaction comes in this category that involves the production of gases due to the interaction of heat and solid substance. Pyrolysis is also an important step in the gasification process and therefore, the gasification reactivity majorly influenced by the pyrolysis process that produces the char, as a feed for the gasification process. Therefore, in the present study, a non-isothermal transient 1-D model is developed for a single biomass pellet to investigate the effect of heat and mass transfer limitations on the rate of pyrolysis reaction. The obtained set of partial differential equations are firstly discretized using the concept of ‘method of lines’ to obtain a set of ordinary differential equation with respect to time. These equations are solved, then, using MATLAB ode solver ode15s. The model is capable of incorporating structural changes, porosity variation, variation in various thermal properties and various pellet shapes. The model is used to analyze the effectiveness factor for different values of Lewis number and heat of reaction (G factor). Lewis number includes the effect of thermal conductivity of the solid pellet. Higher the Lewis number, the higher will be the thermal conductivity of the solid. The effectiveness factor was found to be decreasing with decreasing Lewis number due to the fact that smaller Lewis numbers retard the rate of heat transfer inside the pellet owing to a lower rate of pyrolysis reaction. G factor includes the effect of the heat of reaction. Since the pyrolysis reaction is endothermic in nature, the G factor takes negative values. The more the negative value higher will be endothermic nature of the pyrolysis reaction. The effectiveness factor was found to be decreasing with more negative values of the G factor. This behavior can be attributed to the fact that more negative value of G factor would result in more energy consumption by the reaction owing to a larger temperature gradient inside the pellet. Further, the analytical expressions are also derived for gas and solid concentrations and effectiveness factor for two limiting cases of the general model developed. The two limiting cases of the model are categorized as the homogeneous model and unreacted shrinking core model.Keywords: effectiveness factor, G-factor, homogeneous model, lewis number, non-catalytic, shrinking core model
Procedia PDF Downloads 12145 Performance and Voyage Analysis of Marine Gas Turbine Engine, Installed to Power and Propel an Ocean-Going Cruise Ship from Lagos to Jeddah
Authors: Mathias U. Bonet, Pericles Pilidis, Georgios Doulgeris
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An aero-derivative marine Gas Turbine engine model is simulated to be installed as the main propulsion prime mover to power a cruise ship which is designed and routed to transport intending Muslim pilgrims for the annual hajj pilgrimage from Nigeria to the Islamic port city of Jeddah in Saudi Arabia. A performance assessment of the Gas Turbine engine has been conducted by examining the effect of varying aerodynamic and hydrodynamic conditions encountered at various geographical locations along the scheduled transit route during the voyage. The investigation focuses on the overall behavior of the Gas Turbine engine employed to power and propel the ship as it operates under ideal and adverse conditions to be encountered during calm and rough weather according to the different seasons of the year under which the voyage may be undertaken. The variation of engine performance under varying operating conditions has been considered as a very important economic issue by determining the time the speed by which the journey is completed as well as the quantity of fuel required for undertaking the voyage. The assessment also focuses on the increased resistance caused by the fouling of the submerged portion of the ship hull surface with its resultant effect on the power output of the engine as well as the overall performance of the propulsion system. Daily ambient temperature levels were obtained by accessing data from the UK Meteorological Office while the varying degree of turbulence along the transit route and according to the Beaufort scale were also obtained as major input variables of the investigation. By assuming the ship to be navigating the Atlantic Ocean and the Mediterranean Sea during winter, spring and summer seasons, the performance modeling and simulation was accomplished through the use of an integrated Gas Turbine performance simulation code known as ‘Turbomach’ along with a Matlab generated code named ‘Poseidon’, all of which have been developed at the Power and Propulsion Department of Cranfield University. As a case study, the results of the various assumptions have further revealed that the marine Gas Turbine is a reliable and available alternative to the conventional marine propulsion prime movers that have dominated the maritime industry before now. The techno-economic and environmental assessment of this type of propulsion prime mover has enabled the determination of the effect of changes in weather and sea conditions on the ship speed as well as trip time and the quantity of fuel required to be burned throughout the voyage.Keywords: ambient temperature, hull fouling, marine gas turbine, performance, propulsion, voyage
Procedia PDF Downloads 17744 A Comparison of Proxemics and Postural Head Movements during Pop Music versus Matched Music Videos
Authors: Harry J. Witchel, James Ackah, Carlos P. Santos, Nachiappan Chockalingam, Carina E. I. Westling
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Introduction: Proxemics is the study of how people perceive and use space. It is commonly proposed that when people like or engage with a person/object, they will move slightly closer to it, often quite subtly and subconsciously. Music videos are known to add entertainment value to a pop song. Our hypothesis was that by adding appropriately matched video to a pop song, it would lead to a net approach of the head to the monitor screen compared to simply listening to an audio-only version of the song. Methods: We presented to 27 participants (ages 21.00 ± 2.89, 15 female) seated in front of 47.5 x 27 cm monitor two musical stimuli in a counterbalanced order; all stimuli were based on music videos by the band OK Go: Here It Goes Again (HIGA, boredom ratings (0-100) = 15.00 ± 4.76, mean ± SEM, standard-error-of-the-mean) and Do What You Want (DWYW, boredom ratings = 23.93 ± 5.98), which did not differ in boredom elicited (P = 0.21, rank-sum test). Each participant experienced each song only once, and one song (counterbalanced) as audio-only versus the other song as a music video. The movement was measured by video-tracking using Kinovea 0.8, based on recording from a lateral aspect; before beginning, each participant had a reflective motion tracking marker placed on the outer canthus of the left eye. Analysis of the Kinovea X-Y coordinate output in comma-separated-variables format was performed in Matlab, as were non-parametric statistical tests. Results: We found that the audio-only stimuli (combined for both HIGA and DWYW, mean ± SEM, 35.71 ± 5.36) were significantly more boring than the music video versions (19.46 ± 3.83, P = 0.0066 Wilcoxon Signed Rank Test (WSRT), Cohen's d = 0.658, N = 28). We also found that participants' heads moved around twice as much during the audio-only versions (speed = 0.590 ± 0.095 mm/sec) compared to the video versions (0.301 ± 0.063 mm/sec, P = 0.00077, WSRT). However, the participants' mean head-to-screen distances were not detectably smaller (i.e. head closer to the screen) during the music videos (74.4 ± 1.8 cm) compared to the audio-only stimuli (73.9 ± 1.8 cm, P = 0.37, WSRT). If anything, during the audio-only condition, they were slightly closer. Interestingly, the ranges of the head-to-screen distances were smaller during the music video (8.6 ± 1.4 cm) compared to the audio-only (12.9 ± 1.7 cm, P = 0.0057, WSRT), the standard deviations were also smaller (P = 0.0027, WSRT), and their heads were held 7 mm higher (video 116.1 ± 0.8 vs. audio-only 116.8 ± 0.8 cm above floor, P = 0.049, WSRT). Discussion: As predicted, sitting and listening to experimenter-selected pop music was more boring than when the music was accompanied by a matched, professionally-made video. However, we did not find that the proxemics of the situation led to approaching the screen. Instead, adding video led to efforts to control the head to a more central and upright viewing position and to suppress head fidgeting.Keywords: boredom, engagement, music videos, posture, proxemics
Procedia PDF Downloads 16043 Wheeled Robot Stable Braking Process under Asymmetric Traction Coefficients
Authors: Boguslaw Schreyer
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During the wheeled robot’s braking process, the extra dynamic vertical forces act on all wheels: left, right, front or rear. Those forces are directed downward on the front wheels while directed upward on the rear wheels. In order to maximize the deceleration, therefore, minimize the braking time and braking distance, we need to calculate a correct torque distribution: the front braking torque should be increased, and rear torque should be decreased. At the same time, we need to provide better transversal stability. In a simple case of all adhesion coefficients being the same under all wheels, the torque distribution may secure the optimal (maximal) control of the robot braking process, securing the minimum braking distance and a minimum braking time. At the same time, the transversal stability is relatively good. At any time, we control the transversal acceleration. In the case of the transversal movement, we stop the braking process and re-apply braking torque after a defined period of time. If we correctly calculate the value of the torques, we may secure the traction coefficient under the front and rear wheels close to its maximum. Also, in order to provide an optimum braking control, we need to calculate the timing of the braking torque application and the timing of its release. The braking torques should be released shortly after the wheels passed a maximum traction coefficient (while a wheels’ slip increases) and applied again after the wheels pass a maximum of traction coefficient (while the slip decreases). The correct braking torque distribution secures the front and rear wheels, passing this maximum at the same time. It guarantees an optimum deceleration control, therefore, minimum braking time. In order to calculate a correct torque distribution, a control unit should receive the input signals of a rear torque value (which changes independently), the robot’s deceleration, and values of the vertical front and rear forces. In order to calculate the timing of torque application and torque release, more signals are needed: speed of the robot: angular speed, and angular deceleration of the wheels. In case of different adhesion coefficients under the left and right wheels, but the same under each pair of wheels- the same under right wheels and the same under left wheels, the Select-Low (SL) and select high (SH) methods are applied. The SL method is suggested if transversal stability is more important than braking efficiency. Often in the case of the robot, more important is braking efficiency; therefore, the SH method is applied with some control of the transversal stability. In the case that all adhesion coefficients are different under all wheels, the front-rear torque distribution is maintained as in all previous cases. However, the timing of the braking torque application and release is controlled by the rear wheels’ lowest adhesion coefficient. The Lagrange equations have been used to describe robot dynamics. Matlab has been used in order to simulate the process of wheeled robot braking, and in conclusion, the braking methods have been selected.Keywords: wheeled robots, braking, traction coefficient, asymmetric
Procedia PDF Downloads 15542 The Scenario Analysis of Shale Gas Development in China by Applying Natural Gas Pipeline Optimization Model
Authors: Meng Xu, Alexis K. H. Lau, Ming Xu, Bill Barron, Narges Shahraki
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As an emerging unconventional energy, shale gas has been an economically viable step towards a cleaner energy future in U.S. China also has shale resources that are estimated to be potentially the largest in the world. In addition, China has enormous unmet for a clean alternative to substitute coal. Nonetheless, the geological complexity of China’s shale basins and issues of water scarcity potentially impose serious constraints on shale gas development in China. Further, even if China could replicate to a significant degree the U.S. shale gas boom, China faces the problem of transporting the gas efficiently overland with its limited pipeline network throughput capacity and coverage. The aim of this study is to identify the potential bottlenecks in China’s gas transmission network, as well as to examine the shale gas development affecting particular supply locations and demand centers. We examine this through application of three scenarios with projecting domestic shale gas supply by 2020: optimistic, medium and conservative shale gas supply, taking references from the International Energy Agency’s (IEA’s) projections and China’s shale gas development plans. Separately we project the gas demand at provincial level, since shale gas will have more significant impact regionally than nationally. To quantitatively assess each shale gas development scenario, we formulated a gas pipeline optimization model. We used ArcGIS to generate the connectivity parameters and pipeline segment length. Other parameters are collected from provincial “twelfth-five year” plans and “China Oil and Gas Pipeline Atlas”. The multi-objective optimization model uses GAMs and Matlab. It aims to minimize the demands that are unable to be met, while simultaneously seeking to minimize total gas supply and transmission costs. The results indicate that, even if the primary objective is to meet the projected gas demand rather than cost minimization, there’s a shortfall of 9% in meeting total demand under the medium scenario. Comparing the results between the optimistic and medium supply of shale gas scenarios, almost half of the shale gas produced in Sichuan province and Chongqing won’t be able to be transmitted out by pipeline. On the demand side, the Henan province and Shanghai gas demand gap could be filled as much as 82% and 39% respectively, with increased shale gas supply. To conclude, the pipeline network in China is currently not sufficient in meeting the projected natural gas demand in 2020 under medium and optimistic scenarios, indicating the need for substantial pipeline capacity expansion for some of the existing network, and the importance of constructing new pipelines from particular supply to demand sites. If the pipeline constraint is overcame, Beijing, Shanghai, Jiangsu and Henan’s gas demand gap could potentially be filled, and China could thereby reduce almost 25% its dependency on LNG imports under the optimistic scenario.Keywords: energy policy, energy systematic analysis, scenario analysis, shale gas in China
Procedia PDF Downloads 27641 Selective Conversion of Biodiesel Derived Glycerol to 1,2-Propanediol over Highly Efficient γ-Al2O3 Supported Bimetallic Cu-Ni Catalyst
Authors: Smita Mondal, Dinesh Kumar Pandey, Prakash Biswas
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During past two decades, considerable attention has been given to the value addition of biodiesel derived glycerol (~10wt.%) to make the biodiesel industry economically viable. Among the various glycerol value-addition methods, hydrogenolysis of glycerol to 1,2-propanediol is one of the attractive and promising routes. In this study, highly active and selective γ-Al₂O₃ supported bimetallic Cu-Ni catalyst was developed for selective hydrogenolysis of glycerol to 1,2-propanediol in the liquid phase. The catalytic performance was evaluated in a high-pressure autoclave reactor. The formation of mixed oxide indicated the strong interaction of Cu, Ni with the alumina support. Experimental results demonstrated that bimetallic copper-nickel catalyst was more active and selective to 1,2-PDO as compared to monometallic catalysts due to bifunctional behavior. To verify the effect of calcination temperature on the formation of Cu-Ni mixed oxide phase, the calcination temperature of 20wt.% Cu:Ni(1:1)/Al₂O₃ catalyst was varied from 300°C-550°C. The physicochemical properties of the catalysts were characterized by various techniques such as specific surface area (BET), X-ray diffraction study (XRD), temperature programmed reduction (TPR), and temperature programmed desorption (TPD). The BET surface area and pore volume of the catalysts were in the range of 71-78 m²g⁻¹, and 0.12-0.15 cm³g⁻¹, respectively. The peaks at the 2θ range of 43.3°-45.5° and 50.4°-52°, was corresponded to the copper-nickel mixed oxidephase [JCPDS: 78-1602]. The formation of mixed oxide indicated the strong interaction of Cu, Ni with the alumina support. The crystallite size decreased with increasing the calcination temperature up to 450°C. Further, the crystallite size was increased due to agglomeration. Smaller crystallite size of 16.5 nm was obtained for the catalyst calcined at 400°C. Total acidic sites of the catalysts were determined by NH₃-TPD, and the maximum total acidic of 0.609 mmol NH₃ gcat⁻¹ was obtained over the catalyst calcined at 400°C. TPR data suggested the maximum of 75% degree of reduction of catalyst calcined at 400°C among all others. Further, 20wt.%Cu:Ni(1:1)/γ-Al₂O₃ catalyst calcined at 400°C exhibited highest catalytic activity ( > 70%) and 1,2-PDO selectivity ( > 85%) at mild reaction condition due to highest acidity, highest degree of reduction, smallest crystallite size. Further, the modified Power law kinetic model was developed to understand the true kinetic behaviour of hydrogenolysis of glycerol over 20wt.%Cu:Ni(1:1)/γ-Al₂O₃ catalyst. Rate equations obtained from the model was solved by ode23 using MATLAB coupled with Genetic Algorithm. Results demonstrated that the model predicted data were very well fitted with the experimental data. The activation energy of the formation of 1,2-PDO was found to be 45 kJ mol⁻¹.Keywords: glycerol, 1, 2-PDO, calcination, kinetic
Procedia PDF Downloads 13440 Parametric Analysis of Lumped Devices Modeling Using Finite-Difference Time-Domain
Authors: Felipe M. de Freitas, Icaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende
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The SPICE-based simulators are quite robust and widely used for simulation of electronic circuits, their algorithms support linear and non-linear lumped components and they can manipulate an expressive amount of encapsulated elements. Despite the great potential of these simulators based on SPICE in the analysis of quasi-static electromagnetic field interaction, that is, at low frequency, these simulators are limited when applied to microwave hybrid circuits in which there are both lumped and distributed elements. Usually the spatial discretization of the FDTD (Finite-Difference Time-Domain) method is done according to the actual size of the element under analysis. After spatial discretization, the Courant Stability Criterion calculates the maximum temporal discretization accepted for such spatial discretization and for the propagation velocity of the wave. This criterion guarantees the stability conditions for the leapfrogging of the Yee algorithm; however, it is known that for the field update, the stability of the complete FDTD procedure depends on factors other than just the stability of the Yee algorithm, because the FDTD program needs other algorithms in order to be useful in engineering problems. Examples of these algorithms are Absorbent Boundary Conditions (ABCs), excitation sources, subcellular techniques, grouped elements, and non-uniform or non-orthogonal meshes. In this work, the influence of the stability of the FDTD method in the modeling of concentrated elements such as resistive sources, resistors, capacitors, inductors and diode will be evaluated. In this paper is proposed, therefore, the electromagnetic modeling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-wide frequencies. The models of the resistive source, the resistor, the capacitor, the inductor, and the diode will be evaluated, among the mathematical models for lumped components in the LE-FDTD method (Lumped-Element Finite-Difference Time-Domain), through the parametric analysis of Yee cells size which discretizes the lumped components. In this way, it is sought to find an ideal cell size so that the analysis in FDTD environment is in greater agreement with the expected circuit behavior, maintaining the stability conditions of this method. Based on the mathematical models and the theoretical basis of the required extensions of the FDTD method, the computational implementation of the models in Matlab® environment is carried out. The boundary condition Mur is used as the absorbing boundary of the FDTD method. The validation of the model is done through the comparison between the obtained results by the FDTD method through the electric field values and the currents in the components, and the analytical results using circuit parameters.Keywords: hybrid circuits, LE-FDTD, lumped element, parametric analysis
Procedia PDF Downloads 14539 Design of a Low-Cost, Portable, Sensor Device for Longitudinal, At-Home Analysis of Gait and Balance
Authors: Claudia Norambuena, Myissa Weiss, Maria Ruiz Maya, Matthew Straley, Elijah Hammond, Benjamin Chesebrough, David Grow
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The purpose of this project is to develop a low-cost, portable sensor device that can be used at home for long-term analysis of gait and balance abnormalities. One area of particular concern involves the asymmetries in movement and balance that can accompany certain types of injuries and/or the associated devices used in the repair and rehabilitation process (e.g. the use of splints and casts) which can often increase chances of falls and additional injuries. This device has the capacity to monitor a patient during the rehabilitation process after injury or operation, increasing the patient’s access to healthcare while decreasing the number of visits to the patient’s clinician. The sensor device may thereby improve the quality of the patient’s care, particularly in rural areas where access to the clinician could be limited, while simultaneously decreasing the overall cost associated with the patient’s care. The device consists of nine interconnected accelerometer/ gyroscope/compass chips (9-DOF IMU, Adafruit, New York, NY). The sensors attach to and are used to determine the orientation and acceleration of the patient’s lower abdomen, C7 vertebra (lower neck), L1 vertebra (middle back), anterior side of each thigh and tibia, and dorsal side of each foot. In addition, pressure sensors are embedded in shoe inserts with one sensor (ESS301, Tekscan, Boston, MA) beneath the heel and three sensors (Interlink 402, Interlink Electronics, Westlake Village, CA) beneath the metatarsal bones of each foot. These sensors measure the distribution of the weight applied to each foot as well as stride duration. A small microntroller (Arduino Mega, Arduino, Ivrea, Italy) is used to collect data from these sensors in a CSV file. MATLAB is then used to analyze the data and output the hip, knee, ankle, and trunk angles projected on the sagittal plane. An open-source program Processing is then used to generate an animation of the patient’s gait. The accuracy of the sensors was validated through comparison to goniometric measurements (±2° error). The sensor device was also shown to have sufficient sensitivity to observe various gait abnormalities. Several patients used the sensor device, and the data collected from each represented the patient’s movements. Further, the sensors were found to have the ability to observe gait abnormalities caused by the addition of a small amount of weight (4.5 - 9.1 kg) to one side of the patient. The user-friendly interface and portability of the sensor device will help to construct a bridge between patients and their clinicians with fewer necessary inpatient visits.Keywords: biomedical sensing, gait analysis, outpatient, rehabilitation
Procedia PDF Downloads 27438 The MHz Frequency Range EM Induction Device Development and Experimental Study for Low Conductive Objects Detection
Authors: D. Kakulia, L. Shoshiashvili, G. Sapharishvili
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The results of the study are related to the direction of plastic mine detection research using electromagnetic induction, the development of appropriate equipment, and the evaluation of expected results. Electromagnetic induction sensing is effectively used in the detection of metal objects in the soil and in the discrimination of unexploded ordnances. Metal objects interact well with a low-frequency alternating magnetic field. Their electromagnetic response can be detected at the low-frequency range even when they are placed in the ground. Detection of plastic things such as plastic mines by electromagnetic induction is associated with difficulties. The interaction of non-conducting bodies or low-conductive objects with a low-frequency alternating magnetic field is very weak. At the high-frequency range where already wave processes take place, the interaction increases. Interactions with other distant objects also increase. A complex interference picture is formed, and extraction of useful information also meets difficulties. Sensing by electromagnetic induction at the intermediate MHz frequency range is the subject of research. The concept of detecting plastic mines in this range can be based on the study of the electromagnetic response of non-conductive cavity in a low-conductivity environment or the detection of small metal components in plastic mines, taking into account constructive features. The detector node based on the amplitude and phase detector 'Analog Devices ad8302' has been developed for experimental studies. The node has two inputs. At one of the inputs, the node receives a sinusoidal signal from the generator, to which a transmitting coil is also connected. The receiver coil is attached to the second input of the node. The additional circuit provides an option to amplify the signal output from the receiver coil by 20 dB. The node has two outputs. The voltages obtained at the output reflect the ratio of the amplitudes and the phase difference of the input harmonic signals. Experimental measurements were performed in different positions of the transmitter and receiver coils at the frequency range 1-20 MHz. Arbitrary/Function Generator Tektronix AFG3052C and the eight-channel high-resolution oscilloscope PICOSCOPE 4824 were used in the experiments. Experimental measurements were also performed with a low-conductive test object. The results of the measurements and comparative analysis show the capabilities of the simple detector node and the prospects for its further development in this direction. The results of the experimental measurements are compared and analyzed with the results of appropriate computer modeling based on the method of auxiliary sources (MAS). The experimental measurements are driven using the MATLAB environment. Acknowledgment -This work was supported by Shota Rustaveli National Science Foundation (SRNSF) (Grant number: NFR 17_523).Keywords: EM induction sensing, detector, plastic mines, remote sensing
Procedia PDF Downloads 13637 Air–Water Two-Phase Flow Patterns in PEMFC Microchannels
Authors: Ibrahim Rassoul, A. Serir, E-K. Si Ahmed, J. Legrand
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The acronym PEM refers to Proton Exchange Membrane or alternatively Polymer Electrolyte Membrane. Due to its high efficiency, low operating temperature (30–80 °C), and rapid evolution over the past decade, PEMFCs are increasingly emerging as a viable alternative clean power source for automobile and stationary applications. Before PEMFCs can be employed to power automobiles and homes, several key technical challenges must be properly addressed. One technical challenge is elucidating the mechanisms underlying water transport in and removal from PEMFCs. On one hand, sufficient water is needed in the polymer electrolyte membrane or PEM to maintain sufficiently high proton conductivity. On the other hand, too much liquid water present in the cathode can cause “flooding” (that is, pore space is filled with excessive liquid water) and hinder the transport of the oxygen reactant from the gas flow channel (GFC) to the three-phase reaction sites. The experimental transparent fuel cell used in this work was designed to represent actual full scale of fuel cell geometry. According to the operating conditions, a number of flow regimes may appear in the microchannel: droplet flow, blockage water liquid bridge /plug (concave and convex forms), slug/plug flow and film flow. Some of flow patterns are new, while others have been already observed in PEMFC microchannels. An algorithm in MATLAB was developed to automatically determine the flow structure (e.g. slug, droplet, plug, and film) of detected liquid water in the test microchannels and yield information pertaining to the distribution of water among the different flow structures. A video processing algorithm was developed to automatically detect dynamic and static liquid water present in the gas channels and generate relevant quantitative information. The potential benefit of this software allows the user to obtain a more precise and systematic way to obtain measurements from images of small objects. The void fractions are also determined based on images analysis. The aim of this work is to provide a comprehensive characterization of two-phase flow in an operating fuel cell which can be used towards the optimization of water management and informs design guidelines for gas delivery microchannels for fuel cells and its essential in the design and control of diverse applications. The approach will combine numerical modeling with experimental visualization and measurements.Keywords: polymer electrolyte fuel cell, air-water two phase flow, gas diffusion layer, microchannels, advancing contact angle, receding contact angle, void fraction, surface tension, image processing
Procedia PDF Downloads 29936 Offshore Wind Assessment and Analysis for South Western Mediterranean Sea
Authors: Abdallah Touaibia, Nachida Kasbadji Merzouk, Mustapha Merzouk, Ryma Belarbi
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accuracy assessment and a better understand of the wind resource distribution are the most important tasks for decision making before installing wind energy operating systems in a given region, there where our interest come to the Algerian coastline and its Mediterranean sea area. Despite its large coastline overlooking the border of Mediterranean Sea, there is still no strategy encouraging the development of offshore wind farms in Algerian waters. The present work aims to estimate the offshore wind fields for the Algerian Mediterranean Sea based on wind data measurements ranging from 1995 to 2018 provided of 24 years of measurement by seven observation stations focusing on three coastline cities in Algeria under a different measurement time step recorded from 30 min, 60 min, and 180 min variate from one to each other, two stations in Spain, two other ones in Italy and three in the coast of Algeria from the east Annaba, at the center Algiers, and to Oran taken place at the west of it. The idea behind consists to have multiple measurement points that helping to characterize this area in terms of wind potential by the use of interpolation method of their average wind speed values between these available data to achieve the approximate values of others locations where aren’t any available measurement because of the difficulties against the implementation of masts within the deep depth water. This study is organized as follow: first, a brief description of the studied area and its climatic characteristics were done. After that, the statistical properties of the recorded data were checked by evaluating wind histograms, direction roses, and average speeds using MatLab programs. Finally, ArcGIS and MapInfo soft-wares were used to establish offshore wind maps for better understanding the wind resource distribution, as well as to identify windy sites for wind farm installation and power management. The study pointed out that Cap Carbonara is the windiest site with an average wind speed of 7.26 m/s at 10 m, inducing a power density of 902 W/m², then the site of Cap Caccia with 4.88 m/s inducing a power density of 282 W/m². The average wind speed of 4.83 m/s is occurred for the site of Oran, inducing a power density of 230 W/m². The results indicated also that the dominant wind direction where the frequencies are highest for the site of Cap Carbonara is the West with 34%, an average wind speed of 9.49 m/s, and a power density of 1722 W/m². Then comes the site of Cap Caccia, where the prevailing wind direction is the North-west, about 20% and 5.82 m/s occurring a power density of 452 W/m². The site of Oran comes in third place with the North dominant direction with 32% inducing an average wind speed of 4.59 m/s and power density of 189 W/m². It also shown that the proposed method is either crucial in understanding wind resource distribution for revealing windy sites over a large area and more effective for wind turbines micro-siting.Keywords: wind ressources, mediterranean sea, offshore, arcGIS, mapInfo, wind maps, wind farms
Procedia PDF Downloads 13435 The Influence of Thermal Radiation and Chemical Reaction on MHD Micropolar Fluid in The Presence of Heat Generation/Absorption
Authors: Binyam Teferi
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Numerical and theoretical analysis of mixed convection flow of magneto- hydrodynamics micropolar fluid with stretching capillary in the presence of thermal radiation, chemical reaction, viscous dissipation, and heat generation/ absorption have been studied. The non-linear partial differential equations of momentum, angular velocity, energy, and concentration are converted into ordinary differential equations using similarity transformations which can be solved numerically. The dimensionless governing equations are solved by using Runge Kutta fourth and fifth order along with the shooting method. The effect of physical parameters viz., micropolar parameter, unsteadiness parameter, thermal buoyancy parameter, concentration buoyancy parameter, Hartmann number, spin gradient viscosity parameter, microinertial density parameter, thermal radiation parameter, Prandtl number, Eckert number, heat generation or absorption parameter, Schmidt number and chemical reaction parameter on flow variables viz., the velocity of the micropolar fluid, microrotation, temperature, and concentration has been analyzed and discussed graphically. MATLAB code is used to analyze numerical and theoretical facts. From the simulation study, it can be concluded that an increment of micropolar parameter, Hartmann number, unsteadiness parameter, thermal and concentration buoyancy parameter results in decrement of velocity flow of micropolar fluid; microrotation of micropolar fluid decreases with an increment of micropolar parameter, unsteadiness parameter, microinertial density parameter, and spin gradient viscosity parameter; temperature profile of micropolar fluid decreases with an increment of thermal radiation parameter, Prandtl number, micropolar parameter, unsteadiness parameter, heat absorption, and viscous dissipation parameter; concentration of micropolar fluid decreases as unsteadiness parameter, Schmidt number and chemical reaction parameter increases. Furthermore, computational values of local skin friction coefficient, local wall coupled coefficient, local Nusselt number, and local Sherwood number for different values of parameters have been investigated. In this paper, the following important results are obtained; An increment of micropolar parameter and Hartmann number results in a decrement of velocity flow of micropolar fluid. Microrotation decreases with an increment of the microinertial density parameter. Temperature decreases with an increasing value of the thermal radiation parameter and viscous dissipation parameter. Concentration decreases as the values of Schmidt number and chemical reaction parameter increases. The coefficient of local skin friction is enhanced with an increase in values of both the unsteadiness parameter and micropolar parameter. Increasing values of unsteadiness parameter and micropolar parameter results in an increment of the local couple stress. An increment of values of unsteadiness parameter and thermal radiation parameter results in an increment of the rate of heat transfer. As the values of Schmidt number and unsteadiness parameter increases, Sherwood number decreases.Keywords: thermal radiation, chemical reaction, viscous dissipation, heat absorption/ generation, similarity transformation
Procedia PDF Downloads 12134 Modeling of Geotechnical Data Using GIS and Matlab for Eastern Ahmedabad City, Gujarat
Authors: Rahul Patel, S. P. Dave, M. V Shah
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Ahmedabad is a rapidly growing city in western India that is experiencing significant urbanization and industrialization. With projections indicating that it will become a metropolitan city in the near future, various construction activities are taking place, making soil testing a crucial requirement before construction can commence. To achieve this, construction companies and contractors need to periodically conduct soil testing. This study focuses on the process of creating a spatial database that is digitally formatted and integrated with geotechnical data and a Geographic Information System (GIS). Building a comprehensive geotechnical Geo-database involves three essential steps. Firstly, borehole data is collected from reputable sources. Secondly, the accuracy and redundancy of the data are verified. Finally, the geotechnical information is standardized and organized for integration into the database. Once the Geo-database is complete, it is integrated with GIS. This integration allows users to visualize, analyze, and interpret geotechnical information spatially. Using a Topographic to Raster interpolation process in GIS, estimated values are assigned to all locations based on sampled geotechnical data values. The study area was contoured for SPT N-Values, Soil Classification, Φ-Values, and Bearing Capacity (T/m2). Various interpolation techniques were cross-validated to ensure information accuracy. The GIS map generated by this study enables the calculation of SPT N-Values, Φ-Values, and bearing capacities for different footing widths and various depths. This approach highlights the potential of GIS in providing an efficient solution to complex phenomena that would otherwise be tedious to achieve through other means. Not only does GIS offer greater accuracy, but it also generates valuable information that can be used as input for correlation analysis. Furthermore, this system serves as a decision support tool for geotechnical engineers. The information generated by this study can be utilized by engineers to make informed decisions during construction activities. For instance, they can use the data to optimize foundation designs and improve site selection. In conclusion, the rapid growth experienced by Ahmedabad requires extensive construction activities, necessitating soil testing. This study focused on the process of creating a comprehensive geotechnical database integrated with GIS. The database was developed by collecting borehole data from reputable sources, verifying its accuracy and redundancy, and organizing the information for integration. The GIS map generated by this study is an efficient solution that offers greater accuracy and generates valuable information that can be used as input for correlation analysis. It also serves as a decision support tool for geotechnical engineers, allowing them to make informed decisions during construction activities.Keywords: arcGIS, borehole data, geographic information system (GIS), geo-database, interpolation, SPT N-value, soil classification, φ-value, bearing capacity
Procedia PDF Downloads 6133 Comparison of Two Home Sleep Monitors Designed for Self-Use
Authors: Emily Wood, James K. Westphal, Itamar Lerner
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Background: Polysomnography (PSG) recordings are regularly used in research and clinical settings to study sleep and sleep-related disorders. Typical PSG studies are conducted in professional laboratories and performed by qualified researchers. However, the number of sleep labs worldwide is disproportionate to the increasing number of individuals with sleep disorders like sleep apnea and insomnia. Consequently, there is a growing need to supply cheaper yet reliable means to measure sleep, preferably autonomously by subjects in their own home. Over the last decade, a variety of devices for self-monitoring of sleep became available in the market; however, very few have been directly validated against PSG to demonstrate their ability to perform reliable automatic sleep scoring. Two popular mobile EEG-based systems that have published validation results, the DREEM 3 headband and the Z-Machine, have never been directly compared one to the other by independent researchers. The current study aimed to compare the performance of DREEM 3 and the Z-Machine to help investigators and clinicians decide which of these devices may be more suitable for their studies. Methods: 26 participants have completed the study for credit or monetary compensation. Exclusion criteria included any history of sleep, neurological or psychiatric disorders. Eligible participants arrived at the lab in the afternoon and received the two devices. They then spent two consecutive nights monitoring their sleep at home. Participants were also asked to keep a sleep log, indicating the time they fell asleep, woke up, and the number of awakenings occurring during the night. Data from both devices, including detailed sleep hypnograms in 30-second epochs (differentiating Wake, combined N1/N2, N3; and Rapid Eye Movement sleep), were extracted and aligned upon retrieval. For analysis, the number of awakenings each night was defined as four or more consecutive wake epochs between sleep onset and termination. Total sleep time (TST) and the number of awakenings were compared to subjects’ sleep logs to measure consistency with the subjective reports. In addition, the sleep scores from each device were compared epoch-by-epoch to calculate the agreement between the two devices using Cohen’s Kappa. All analysis was performed using Matlab 2021b and SPSS 27. Results/Conclusion: Subjects consistently reported longer times spent asleep than the time reported by each device (M= 448 minutes for sleep logs compared to M= 406 and M= 345 minutes for the DREEM and Z-Machine, respectively; both ps<0.05). Linear correlations between the sleep log and each device were higher for the DREEM than the Z-Machine for both TST and the number of awakenings, and, likewise, the mean absolute bias between the sleep logs and each device was higher for the Z-Machine for both TST (p<0.001) and awakenings (p<0.04). There was some indication that these effects were stronger for the second night compared to the first night. Epoch-by-epoch comparisons showed that the main discrepancies between the devices were for detecting N2 and REM sleep, while N3 had a high agreement. Overall, the DREEM headband seems superior for reliably scoring sleep at home.Keywords: DREEM, EEG, seep monitoring, Z-machine
Procedia PDF Downloads 9932 Applying Biosensors’ Electromyography Signals through an Artificial Neural Network to Control a Small Unmanned Aerial Vehicle
Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores
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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino
Procedia PDF Downloads 16531 Perception of Tactile Stimuli in Children with Autism Spectrum Disorder
Authors: Kseniya Gladun
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Tactile stimulation of a dorsal side of the wrist can have a strong impact on our attitude toward physical objects such as pleasant and unpleasant impact. This study explored different aspects of tactile perception to investigate atypical touch sensitivity in children with autism spectrum disorder (ASD). This study included 40 children with ASD and 40 healthy children aged 5 to 9 years. We recorded rsEEG (sampling rate of 250 Hz) during 20 min using EEG amplifier “Encephalan” (Medicom MTD, Taganrog, Russian Federation) with 19 AgCl electrodes placed according to the International 10–20 System. The electrodes placed on the left, and right mastoids served as joint references under unipolar montage. The registration of EEG v19 assignments was carried out: frontal (Fp1-Fp2; F3-F4), temporal anterior (T3-T4), temporal posterior (T5-T6), parietal (P3-P4), occipital (O1-O2). Subjects were passively touched by 4 types of tactile stimuli on the left wrist. Our stimuli were presented with a velocity of about 3–5 cm per sec. The stimuli materials and procedure were chosen for being the most "pleasant," "rough," "prickly" and "recognizable". Type of tactile stimulation: Soft cosmetic brush - "pleasant" , Rough shoe brush - "rough", Wartenberg pin wheel roller - "prickly", and the cognitive tactile stimulation included letters by finger (most of the patient’s name ) "recognizable". To designate the moments of the stimuli onset-offset, we marked the moment when the moment of the touch began and ended; the stimulation was manual, and synchronization was not precise enough for event-related measures. EEG epochs were cleaned from eye movements by ICA-based algorithm in EEGLAB plugin for MatLab 7.11.0 (Mathwork Inc.). Muscle artifacts were cut out by manual data inspection. The response to tactile stimuli was significantly different in the group of children with ASD and healthy children, which was also depended on type of tactile stimuli and the severity of ASD. Amplitude of Alpha rhythm increased in parietal region to response for only pleasant stimulus, for another type of stimulus ("rough," "thorny", "recognizable") distinction of amplitude was not observed. Correlation dimension D2 was higher in healthy children compared to children with ASD (main effect ANOVA). In ASD group D2 was lower for pleasant and unpleasant compared to the background in the right parietal area. Hilbert transform changes in the frequency of the theta rhythm found only for a rough tactile stimulation compared with healthy participants only in the right parietal area. Children with autism spectrum disorders and healthy children were responded to tactile stimulation differently with specific frequency distribution alpha and theta band in the right parietal area. Thus, our data supports the hypothesis that rsEEG may serve as a sensitive index of altered neural activity caused by ASD. Children with autism have difficulty in distinguishing the emotional stimuli ("pleasant," "rough," "prickly" and "recognizable").Keywords: autism, tactile stimulation, Hilbert transform, pediatric electroencephalography
Procedia PDF Downloads 24430 A Biophysical Study of the Dynamic Properties of Glucagon Granules in α Cells by Imaging-Derived Mean Square Displacement and Single Particle Tracking Approaches
Authors: Samuele Ghignoli, Valentina de Lorenzi, Gianmarco Ferri, Stefano Luin, Francesco Cardarelli
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Insulin and glucagon are the two essential hormones for maintaining proper blood glucose homeostasis, which is disrupted in Diabetes. A constantly growing research interest has been focused on the study of the subcellular structures involved in hormone secretion, namely insulin- and glucagon-containing granules, and on the mechanisms regulating their behaviour. Yet, while several successful attempts were reported describing the dynamic properties of insulin granules, little is known about their counterparts in α cells, the glucagon-containing granules. To fill this gap, we used αTC1 clone 9 cells as a model of α cells and ZIGIR as a fluorescent Zinc chelator for granule labelling. We started by using spatiotemporal fluorescence correlation spectroscopy in the form of imaging-derived mean square displacement (iMSD) analysis. This afforded quantitative information on the average dynamical and structural properties of glucagon granules having insulin granules as a benchmark. Interestingly, the iMSD sensitivity to average granule size allowed us to confirm that glucagon granules are smaller than insulin ones (~1.4 folds, further validated by STORM imaging). To investigate possible heterogeneities in granule dynamic properties, we moved from correlation spectroscopy to single particle tracking (SPT). We developed a MATLAB script to localize and track single granules with high spatial resolution. This enabled us to classify the glucagon granules, based on their dynamic properties, as ‘blocked’ (i.e., trajectories corresponding to immobile granules), ‘confined/diffusive’ (i.e., trajectories corresponding to slowly moving granules in a defined region of the cell), or ‘drifted’ (i.e., trajectories corresponding to fast-moving granules). In cell-culturing control conditions, results show this average distribution: 32.9 ± 9.3% blocked, 59.6 ± 9.3% conf/diff, and 7.4 ± 3.2% drifted. This benchmarking provided us with a foundation for investigating selected experimental conditions of interest, such as the glucagon-granule relationship with the cytoskeleton. For instance, if Nocodazole (10 μM) is used for microtubule depolymerization, the percentage of drifted motion collapses to 3.5 ± 1.7% while immobile granules increase to 56.0 ± 10.7% (remaining 40.4 ± 10.2% of conf/diff). This result confirms the clear link between glucagon-granule motion and cytoskeleton structures, a first step towards understanding the intracellular behaviour of this subcellular compartment. The information collected might now serve to support future investigations on glucagon granules in physiology and disease. Acknowledgment: This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 866127, project CAPTUR3D).Keywords: glucagon granules, single particle tracking, correlation spectroscopy, ZIGIR
Procedia PDF Downloads 8929 Flow Visualization and Mixing Enhancement in Y-Junction Microchannel with 3D Acoustic Streaming Flow Patterns Induced by Trapezoidal Triangular Structure using High-Viscous Liquids
Authors: Ayalew Yimam Ali
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The Y-shaped microchannel system is used to mix up low or high viscosities of different fluids, and the laminar flow with high-viscous water-glycerol fluids makes the mixing at the entrance Y-junction region a challenging issue. Acoustic streaming (AS) is time-average, a steady second-order flow phenomenon that could produce rolling motion in the microchannel by oscillating low-frequency range acoustic transducer by inducing acoustic wave in the flow field is the promising strategy to enhance diffusion mass transfer and mixing performance in laminar flow phenomena. In this study, the 3D trapezoidal Structure has been manufactured with advanced CNC machine cutting tools to produce the molds of trapezoidal structure with the 3D sharp edge tip angles of 30° and 0.3mm spine sharp-edge tip depth from PMMA glass (Polymethylmethacrylate) and the microchannel has been fabricated using PDMS (Polydimethylsiloxane) which could be grown-up longitudinally in Y-junction microchannel mixing region top surface to visualized 3D rolling steady acoustic streaming and mixing performance evaluation using high-viscous miscible fluids. The 3D acoustic streaming flow patterns and mixing enhancement were investigated using the micro-particle image velocimetry (μPIV) technique with different spine depth lengths, channel widths, high volume flow rates, oscillation frequencies, and amplitude. The velocity and vorticity flow fields show that a pair of 3D counter-rotating streaming vortices were created around the trapezoidal spine structure and observing high vorticity maps up to 8 times more than the case without acoustic streaming in Y-junction with the high-viscosity water-glycerol mixture fluids. The mixing experiments were performed by using fluorescent green dye solution with de-ionized water on one inlet side, de-ionized water-glycerol with different mass-weight percentage ratios on the other inlet side of the Y-channel and evaluated its performance with the degree of mixing at different amplitudes, flow rates, frequencies, and spine sharp-tip edge angles using the grayscale value of pixel intensity with MATLAB Software. The degree of mixing (M) characterized was found to significantly improved to 0.96.8% with acoustic streaming from 67.42% without acoustic streaming, in the case of 0.0986 μl/min flow rate, 12kHz frequency and 40V oscillation amplitude at y = 2.26 mm. The results suggested the creation of a new 3D steady streaming rolling motion with a high volume flow rate around the entrance junction mixing region, which promotes the mixing of two similar high-viscosity fluids inside the microchannel, which is unable to mix by the laminar flow with low viscous conditions.Keywords: nano fabrication, 3D acoustic streaming flow visualization, micro-particle image velocimetry, mixing enhancement
Procedia PDF Downloads 1028 Experimental Study of Energy Absorption Efficiency (EAE) of Warp-Knitted Spacer Fabric Reinforced Foam (WKSFRF) Under Low-Velocity Impact
Authors: Amirhossein Dodankeh, Hadi Dabiryan, Saeed Hamze
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Using fabrics to reinforce composites considerably leads to improved mechanical properties, including resistance to the impact load and the energy absorption of composites. Warp-knitted spacer fabrics (WKSF) are fabrics consisting of two layers of warp-knitted fabric connected by pile yarns. These connections create a space between the layers filled by pile yarns and give the fabric a three-dimensional shape. Today because of the unique properties of spacer fabrics, they are widely used in the transportation, construction, and sports industries. Polyurethane (PU) foams are commonly used as energy absorbers, but WKSF has much better properties in moisture transfer, compressive properties, and lower heat resistance than PU foam. It seems that the use of warp-knitted spacer fabric reinforced PU foam (WKSFRF) can lead to the production and use of composite, which has better properties in terms of energy absorption from the foam, its mold formation is enhanced, and its mechanical properties have been improved. In this paper, the energy absorption efficiency (EAE) of WKSFRF under low-velocity impact is investigated experimentally. The contribution of the effect of each of the structural parameters of the WKSF on the absorption of impact energy has also been investigated. For this purpose, WKSF with different structures such as two different thicknesses, small and large mesh sizes, and position of the meshes facing each other and not facing each other were produced. Then 6 types of composite samples with different structural parameters were fabricated. The physical properties of samples like weight per unit area and fiber volume fraction of composite were measured for 3 samples of any type of composites. Low-velocity impact with an initial energy of 5 J was carried out on 3 samples of any type of composite. The output of the low-velocity impact test is acceleration-time (A-T) graph with a lot deviation point, in order to achieve the appropriate results, these points were removed using the FILTFILT function of MATLAB R2018a. Using Newtonian laws of physics force-displacement (F-D) graph was drawn from an A-T graph. We know that the amount of energy absorbed is equal to the area under the F-D curve. Determination shows the maximum energy absorption is 2.858 J which is related to the samples reinforced with fabric with large mesh, high thickness, and not facing of the meshes relative to each other. An index called energy absorption efficiency was defined, which means absorption energy of any kind of our composite divided by its fiber volume fraction. With using this index, the best EAE between the samples is 21.6 that occurs in the sample with large mesh, high thickness, and meshes facing each other. Also, the EAE of this sample is 15.6% better than the average EAE of other composite samples. Generally, the energy absorption on average has been increased 21.2% by increasing the thickness, 9.5% by increasing the size of the meshes from small to big, and 47.3% by changing the position of the meshes from facing to non-facing.Keywords: composites, energy absorption efficiency, foam, geometrical parameters, low-velocity impact, warp-knitted spacer fabric
Procedia PDF Downloads 16127 Simulation of Hydraulic Fracturing Fluid Cleanup for Partially Degraded Fracturing Fluids in Unconventional Gas Reservoirs
Authors: Regina A. Tayong, Reza Barati
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A stable, fast and robust three-phase, 2D IMPES simulator has been developed for assessing the influence of; breaker concentration on yield stress of filter cake and broken gel viscosity, varying polymer concentration/yield stress along the fracture face, fracture conductivity, fracture length, capillary pressure changes and formation damage on fracturing fluid cleanup in tight gas reservoirs. This model has been validated as against field data reported in the literature for the same reservoir. A 2-D, two-phase (gas/water) fracture propagation model is used to model our invasion zone and create the initial conditions for our clean-up model by distributing 200 bbls of water around the fracture. A 2-D, three-phase IMPES simulator, incorporating a yield-power-law-rheology has been developed in MATLAB to characterize fluid flow through a hydraulically fractured grid. The variation in polymer concentration along the fracture is computed from a material balance equation relating the initial polymer concentration to total volume of injected fluid and fracture volume. All governing equations and the methods employed have been adequately reported to permit easy replication of results. The effect of increasing capillary pressure in the formation simulated in this study resulted in a 10.4% decrease in cumulative production after 100 days of fluid recovery. Increasing the breaker concentration from 5-15 gal/Mgal on the yield stress and fluid viscosity of a 200 lb/Mgal guar fluid resulted in a 10.83% increase in cumulative gas production. For tight gas formations (k=0.05 md), fluid recovery increases with increasing shut-in time, increasing fracture conductivity and fracture length, irrespective of the yield stress of the fracturing fluid. Mechanical induced formation damage combined with hydraulic damage tends to be the most significant. Several correlations have been developed relating pressure distribution and polymer concentration to distance along the fracture face and average polymer concentration variation with injection time. The gradient in yield stress distribution along the fracture face becomes steeper with increasing polymer concentration. The rate at which the yield stress (τ_o) is increasing is found to be proportional to the square of the volume of fluid lost to the formation. Finally, an improvement on previous results was achieved through simulating yield stress variation along the fracture face rather than assuming constant values because fluid loss to the formation and the polymer concentration distribution along the fracture face decreases as we move away from the injection well. The novelty of this three-phase flow model lies in its ability to (i) Simulate yield stress variation with fluid loss volume along the fracture face for different initial guar concentrations. (ii) Simulate increasing breaker activity on yield stress and broken gel viscosity and the effect of (i) and (ii) on cumulative gas production within reasonable computational time.Keywords: formation damage, hydraulic fracturing, polymer cleanup, multiphase flow numerical simulation
Procedia PDF Downloads 11626 Classification of ECG Signal Based on Mixture of Linear and Non-Linear Features
Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh
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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve
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