Search results for: gradient constancy assumption.

Authors: M. R. AlRashidi, M. F. AlHajri, M. E. El-Hawary

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An enhanced particle swarm optimization algorithm (PSO) is presented in this work to solve the non-convex OPF problem that has both discrete and continuous optimization variables. The objective functions considered are the conventional quadratic function and the augmented quadratic function. The latter model presents non-differentiable and non-convex regions that challenge most gradient-based optimization algorithms. The optimization variables to be optimized are the generator real power outputs and voltage magnitudes, discrete transformer tap settings, and discrete reactive power injections due to capacitor banks. The set of equality constraints taken into account are the power flow equations while the inequality ones are the limits of the real and reactive power of the generators, voltage magnitude at each bus, transformer tap settings, and capacitor banks reactive power injections. The proposed algorithm combines PSO with Newton-Raphson algorithm to minimize the fuel cost function. The IEEE 30-bus system with six generating units is used to test the proposed algorithm. Several cases were investigated to test and validate the consistency of detecting optimal or near optimal solution for each objective. Results are compared to solutions obtained using sequential quadratic programming and Genetic Algorithms.

Keywords: Particle Swarm Optimization, Optimal Power Flow, Economic Dispatch.

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Authors: Teh Raihana Nazirah Roslan, Siti Zulaiha Ibrahim, Sharmila Karim

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A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study.

Keywords: Cox-Ingersoll-Ross model, equity warrants, Heston model, hybrid models, stochastic.

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Authors: Jahan Zeb, Muhammad Younus Javed, Usman Qayyum

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This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.

Keywords: Average filtering, Bicubic Interpolation, Neurons, vectorization.

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Authors: C. Villegas-Quezada, J. Climent

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Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.

Keywords: AdaBoost Classifier, Holistic Face Recognition, Minimax Multivariate Approximation, Genetic Algorithm.

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Authors: Maha Salah Abdullah Ismail, Mahmoud M. Alsagheir, Mohammed Salah Abd Allah

Abstract:

Acute respiratory distress syndrome (ARDS) is characterized by permeability pulmonary edema and refractory hypoxemia. Lung-protective ventilation is still the key of better outcome in ARDS. Prone position reduces the trans-pulmonary pressure gradient, recruiting collapsed regions of the lung without increasing airway pressure or hyperinflation. Prone ventilation showed improved oxygenation and improved outcomes in severe hypoxemic patients with ARDS. This study evaluates the effect of prone positioning on mechanically ventilated patients with ARDS. A quasi-experimental design was carried out at Critical Care Units, on 60 patients. Two tools were utilized to collect data; Socio demographic, medical and clinical outcomes data sheet. Results of the present study indicated that prone position improves oxygenation in patients with severe respiratory distress syndrome. The study recommended that use prone position in patients with severe ARDS, as early as possible and for long sessions. Also, replication of this study on larger probability sample at the different geographical location is highly recommended.

Keywords: Acute respiratory distress syndrome, Critical care, Mechanical ventilation and Prone position.

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Authors: M. A. Askari, M. A. Nazari, P. Perrier, Y. Payan

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Growth and remodeling of biological structures have gained lots of attention over the past decades. Determining the response of living tissues to mechanical loads is necessary for a wide range of developing fields such as prosthetics design or computerassisted surgical interventions. It is a well-known fact that biological structures are never stress-free, even when externally unloaded. The exact origin of these residual stresses is not clear, but theoretically, growth is one of the main sources. Extracting body organ’s shapes from medical imaging does not produce any information regarding the existing residual stresses in that organ. The simplest cause of such stresses is gravity since an organ grows under its influence from birth. Ignoring such residual stresses might cause erroneous results in numerical simulations. Accounting for residual stresses due to tissue growth can improve the accuracy of mechanical analysis results. This paper presents an original computational framework based on gradual growth to determine the residual stresses due to growth. To illustrate the method, we apply it to a finite element model of a healthy human face reconstructed from medical images. The distribution of residual stress in facial tissues is computed, which can overcome the effect of gravity and maintain tissues firmness. Our assumption is that tissue wrinkles caused by aging could be a consequence of decreasing residual stress and thus not counteracting gravity. Taking into account these stresses seems therefore extremely important in maxillofacial surgery. It would indeed help surgeons to estimate tissues changes after surgery.

Keywords: Finite element method, growth, residual stress, soft tissue.

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Authors: Iau-Teh Wang, Chin-Yu Lee

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Rockfall is a kind of irregular geological disaster. Its destruction time, space and movements are highly random. The impact force is determined by the way and velocity rocks move. The movement velocity of a rockfall depends on slope gradient of its moving paths, height, slope surface roughness and rock shapes. For effectively mitigate and prevent disasters brought by rockfalls, it is required to precisely calculate the moving paths of a rockfall so as to provide the best protective design. This paper applies Colorado Rockfall Simulation Program (CRSP) as our study tool to discuss the impact of slope shape and surface roughness on the moving paths of a single rockfall. The analytical results showed that the slope, m=1:1, acted as the threshold for rockfall bounce height on a monoclinal slight slope. When JRC ´╝£ 1.2, movement velocity reduced and bounce height increased as JCR increased. If slope fixed and JRC increased, the bounce height of rocks increased gradually with reducing movement velocity. Therefore, the analysis on the moving paths of rockfalls with CRSP could simulate bouncing of falling rocks. By analyzing moving paths, velocity, and bounce height of falling rocks, we could effectively locate impact points of falling rocks on a slope. Such analysis can be served as a reference for future disaster prevention and control.

Keywords: Rockfall, Slope Shape, Moving Path, SurfaceRoughness.

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Authors: M. Tarawneh

Abstract:

Two-phase frictional pressure drop data were obtained for condensation of carbon dioxide in single horizontal micro tube of inner diameter ranged from 0.6 mm up to 1.6 mm over mass flow rates from 2.5*10-5 to 17*10-5 kg/s and vapor qualities from 0.0 to 1.0. The inlet condensing pressure is changed from 33.5 to 45 bars. The saturation temperature ranged from -1.5 oC up to 10 oC. These data have then been compared against three (two-phase) frictional pressure drop prediction methods. The first method is by Muller-Steinhagen and Heck (Muller-Steinhagen H, Heck K. A simple friction pressure drop correlation for two-phase flow in pipes. Chem. Eng. Process 1986;20:297–308) and that by Gronnerud R. Investigation of liquid hold-up, flow-resistance and heat transfer in circulation type evaporators, part IV: two-phase flow resistance in boiling refrigerants, Annexe 1972. Then the method used by FriedelL. Improved friction pressures drop in horizontal and vertical two-phase pipe flow. European Two-Phase Flow Group Meeting, Paper E2; 1979 June, Ispra, Italy. The methods are used by M.B Ould Didi et al (2001) “Prediction of two-phase pressure gradients of refrigerant in horizontal tubes". Int.J.of Refrigeration 25(2002) 935- 947. The best available method for annular flow was that of Muller- Steinhagen and Heck. It was observed that the peak in the two-phase frictional pressure gradient is at high vapor qualities.

Keywords: Two-phase flow, frictional pressure drop, horizontalmicro tube, carbon dioxide, condensers.

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Authors: Andrew Jester, Ross Lee, Pritpal Singh

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As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, a new battery technology is desirable for grid applications to curtail these risks. Biological cells, such as human neurons and electrocytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell akin to the charging/discharging of a battery cell. This work serves as the first step for developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na+-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior like human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: Battery, biomimetic, electrocytes, human neurons, ion-selective membranes, membrane potential.

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Authors: Bakari M. M. Mwinyiwiwa, Mighanda J. Manyahi, Nicodemu Gregory, Alex L. Kyaruzi

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Microgrids are increasingly being considered to provide electricity for the expanding energy demand in the grid distribution network and grid isolated areas. However, the technical challenges associated with the operation and controls are immense. Management of dynamic power balances, power flow, and network voltage profiles imposes unique challenges in the context of microgrids. Stability of the microgrid during both grid-connected and islanded mode is considered as the major challenge during its operation. Traditional control methods have been employed are based on the assumption of linear loads. For instance the concept of PQ, voltage and frequency control through decoupled PQ are some of very useful when considering linear loads, but they fall short when considering nonlinear loads. The deficiency of traditional control methods of microgrid suggests that more research in the control of microgrids should be done. This research aims at introducing the dq technique concept into decoupled PQ for dynamic load demand control in inverter interfaced DG system operating as isolated LV microgrid. Decoupled PQ in exact mathematical formulation in dq frame is expected to accommodate all variations of the line parameters (resistance and inductance) and to relinquish forced relationship between the DG variables such as power, voltage and frequency in LV microgrids and allow for individual parameter control (frequency and line voltages). This concept is expected to address and achieve accurate control, improve microgrid stability and power quality at all load conditions.

Keywords: Decoupled PQ, microgrid, multisource, renewable energy, dq control.

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.

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Authors: Ahmad Fahim Nasiry, Shigeo Honma

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We examine two-dimensional oil displacement by water in a petroleum reservoir. The pore fluid is immiscible, and the porous media is homogenous and isotropic in the horizontal direction. Buckley-Leverett theory and a combination of Laplacian and Darcy’s law are used to study the fluid flow through porous media, and the Laplacian that defines the dispersion and diffusion of fluid in the sand using heavy oil is discussed. The reservoir is homogenous in the horizontal direction, as expressed by the partial differential equation. Two main factors which are observed are the water saturation and pressure distribution in the reservoir, and they are evaluated for predicting oil recovery in two dimensions by a physical and mathematical simulation model. We review the numerical simulation that solves difficult partial differential reservoir equations. Based on the numerical simulations, the saturation and pressure equations are calculated by the iterative alternating direction implicit method and the iterative alternating direction explicit method, respectively, according to the finite difference assumption. However, to understand the displacement of oil by water and the amount of water dispersion in the reservoir better, an interpolated contour line of the water distribution of the five-spot pattern, that provides an approximate solution which agrees well with the experimental results, is also presented. Finally, a computer program is developed to calculate the equation for pressure and water saturation and to draw the pressure contour line and water distribution contour line for the reservoir.

Keywords: Numerical simulation, immiscible, finite difference, IADI, IADE, waterflooding.

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Authors: Barenten Suciu

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In this work, effects of the friction and truncation on the dynamics of a double-cone gravitational motor, self-propelled on a straight V-shaped horizontal rail, are evaluated. Such mechanism has a variable radius of contact, and, on one hand, it is similar to a pulley mechanism that changes the potential energy into the kinetic energy of rotation, but on the other hand, it is similar to a pendulum mechanism that converts the potential energy of the suspended body into the kinetic energy of translation along a circular path. Movies of the self- propelled double-cones, made of S45C carbon steel and wood, along rails made of aluminum alloy, were shot for various opening angles of the rails. Kinematical features of the double-cones were estimated through the slow-motion processing of the recorded movies. Then, a kinematical model is derived under assumption that the distance traveled by the contact points on the rectilinear rails is identical with the distance traveled by the contact points on the truncated conical surface. Additionally, a dynamic model, for this particular contact problem, was proposed and validated against the experimental results. Based on such model, the traction force and the traction torque acting on the double-cone are identified. One proved that the rolling traction force is always smaller than the sliding friction force; i.e., the double-cone is rolling without slipping. Results obtained in this work can be used to achieve the proper design of such gravitational motor.

Keywords: Truncated double-cone, friction, rolling and sliding, dynamic model, gravitational motor.

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Authors: Asad Islam, Khalid Parvez

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Compressor fans in modern aircraft engines are of considerate importance, as they provide majority of thrust required by the aircraft. Their challenging environment is frequently subjected to non-uniform inflow conditions. These conditions could be either due to the flight operating requirements such as take-off and landing, wake interference from aircraft fuselage or cross-flow wind conditions. So, in highly maneuverable flights regimes of fighter aircrafts affects the overall performance of an engine. Since the flow in compressor of an aircraft application is highly sensitive because of adverse pressure gradient due to different flow orientations of the aircraft. Therefore, it is prone to unstable operations. This paper presents the study that focuses on axial compressor response to inlet flow orientations for the range of angles as 0 to 15 degrees. For this purpose, NASA Rotor-37 was taken and CFD mesh was developed. The compressor characteristics map was generated for the design conditions of pressure ratio of 2.106 with the rotor operating at rotational velocity of 17188.7 rpm using CFD simulating environment of ANSYS-CFX®. The grid study was done to see the effects of mesh upon computational solution. Then, the mesh giving the best results, (when validated with the available experimental NASA’s results); was used for further distortion analysis. The flow in the inlet nozzle was given angle orientations ranging from 0 to 15 degrees. The CFD results are analyzed and discussed with respect to stall margin and flow separations due to induced distortions.

Keywords: Angle, ANSYS-CFX®, axial compressor, Bladegen®, CFD, distortions.

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence.

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Authors: Sangeeta Mandal, Rajib Kar, Durbadal Mandal, Sakti Prasad Ghoshal

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In this paper, an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach (PSO-CFIWA) has been presented. In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. The conventional gradient based optimization techniques are not efficient for digital filter design. Given the filter specifications to be realized, the PSO-CFIWA algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristic. In this paper, for the given problem, the designs of the optimal FIR high pass filters of different orders have been performed. The simulation results have been compared to those obtained by the well accepted algorithms such as Parks and McClellan algorithm (PM), genetic algorithm (GA). The results justify that the proposed optimal filter design approach using PSOCFIWA outperforms PM and GA, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.

Keywords: FIR Filter; PSO-CFIWA; PSO; Parks and McClellanAlgorithm, Evolutionary Optimization Technique; MagnitudeResponse; Convergence; High Pass Filter

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Authors: Satyanadh Gundimada, Vijayan K Asari

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A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.

Keywords: Discriminant analysis, intra-class probability distribution, principal component analysis, phase congruency.

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

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

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

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Authors: Omid Ghasemalizadeh, Mohammad Reza Mirzaee, Hossein Sadeghi, Mohammad Taghi Ahmadian

Abstract:

There are lots of different ways to find the natural frequencies of a rotating system. One of the most effective methods which is used because of its precision and correctness is the application of the transfer matrix. By use of this method the entire continuous system is subdivided and the corresponding differential equation can be stated in matrix form. So to analyze shaft that is this paper issue the rotor is divided as several elements along the shaft which each one has its own mass and moment of inertia, which this work would create possibility of defining the named matrix. By Choosing more elements number, the size of matrix would become larger and as a result more accurate answers would be earned. In this paper the dynamics of a rotor-bearing system is analyzed, considering the gyroscopic effect. To increase the accuracy of modeling the thickness of the disk and bearings is also taken into account which would cause more complicated matrix to be solved. Entering these parameters to our modeling would change the results completely that these differences are shown in the results. As said upper, to define transfer matrix to reach the natural frequencies of probed system, introducing some elements would be one of the requirements. For the boundary condition of these elements, bearings at the end of the shaft are modeled as equivalent spring and dampers for the discretized system. Also, continuous model is used for the shaft in the system. By above considerations and using transfer matrix, exact results are taken from the calculations. Results Show that, by increasing thickness of the bearing the amplitude of vibration would decrease, but obviously the stiffness of the shaft and the natural frequencies of the system would accompany growth. Consequently it is easily understood that ignoring the influences of bearing and disk thicknesses would results not real answers.

Keywords: Rotor System, Disk and Bearing Thickness, Transfer Matrix, Amplitude.

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Authors: Nidhal Jamia, Sami El-Borgi

Abstract:

In this paper, the problem of a mixed-Mode crack embedded in an infinite medium made of a functionally graded piezoelectric material (FGPM) with crack surfaces subjected to electro-mechanical loadings is investigated. Eringen’s non-local theory of elasticity is adopted to formulate the governing electro-elastic equations. The properties of the piezoelectric material are assumed to vary exponentially along a perpendicular plane to the crack. Using Fourier transform, three integral equations are obtained in which the unknown variables are the jumps of mechanical displacements and electric potentials across the crack surfaces. To solve the integral equations, the unknowns are directly expanded as a series of Jacobi polynomials, and the resulting equations solved using the Schmidt method. In contrast to the classical solutions based on the local theory, it is found that no mechanical stress and electric displacement singularities are present at the crack tips when nonlocal theory is employed to investigate the problem. A direct benefit is the ability to use the calculated maximum stress as a fracture criterion. The primary objective of this study is to investigate the effects of crack length, material gradient parameter describing FGPMs, and lattice parameter on the mechanical stress and electric displacement field near crack tips.

Keywords: Functionally graded piezoelectric material, mixed-mode crack, non-local theory, Schmidt method.

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Authors: Seema Chopra, R. Mitra, Vijay Kumar

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A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.

Keywords: Fuzzy control, neuro-fuzzy techniques, fuzzy subtractive clustering, extraction of rules, and optimization of membership functions.

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Authors: Daohong Yang, Xiang Zhang, Wanting Zhou, Lei Li

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Visual Simultaneous Localization and Mapping (VSLAM) is a technology that gathers information about the surrounding environment to ascertain its own position and create a map. It is widely used in computer vision, robotics, and various other fields. Many visual SLAM systems, such as OBSLAM3, utilize a constant velocity motion model. The utilization of this model facilitates the determination of the initial pose of the current frame, thereby enhancing the efficiency and precision of feature matching. However, it is often difficult to satisfy the constant velocity motion model in actual situations. This can result in a significant deviation between the obtained initial pose and the true value, leading to errors in nonlinear optimization results. Therefore, this paper proposes a motion model based on acceleration that can be applied to most SLAM systems. To provide a more accurate description of the camera pose acceleration, we separate the pose transformation matrix into its rotation matrix and translation vector components. The rotation matrix is now represented by a rotation vector. We assume that, over a short period, the changes in rotating angular velocity and translation vector remain constant. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of the constant velocity model is analyzed theoretically. Finally, we apply our proposed approach to the ORBSLAM3 system and evaluate two sets of sequences from the TUM datasets. The results show that our proposed method has a more accurate initial pose estimation, resulting in an improvement of 6.61% and 6.46% in the accuracy of the ORBSLAM3 system on the two test sequences, respectively.

Keywords: Error estimation, constant acceleration motion model, pose estimation, visual SLAM.

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Authors: S. A. Moeini, M. T.Ahmadian

Abstract:

Structural behavior of ring stiffened thick walled cylinders made of functionally graded materials (FGMs) is investigated in this paper. Functionally graded materials are inhomogeneous composites which are usually made from a mixture of metal and ceramic. The gradient compositional variation of the constituents from one surface to the other provides an elegant solution to the problem of high transverse shear stresses that are induced when two dissimilar materials with large differences in material properties are bonded. FGM formation of the cylinder is modeled by power-law exponent and the variation of characteristics is supposed to be in radial direction. A finite element formulation is derived for the analysis. According to the property variation of the constituent materials in the radial direction of the wall, it is not convenient to use conventional elements to model and analyze the structure of the stiffened FGM cylinders. In this paper a new cylindrical super-element is used to model the finite element formulation and analyze the static and modal behavior of stiffened FGM thick walled cylinders. By using this super-element the number of elements, which are needed for modeling, will reduce significantly and the process time is less in comparison with conventional finite element formulations. Results for static and modal analysis are evaluated and verified by comparison to finite element formulation with conventional elements. Comparison indicates a good conformity between results.

Keywords: FGMs, Modal analysis, Static analysis, Stiffened cylinders.

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Authors: Olimpia Matarazzo, Fabrizio Ferrara

Abstract:

In two studies we tested the hypothesis that the appropriate linguistic formulation of a deontic rule – i.e. the formulation which clarifies the monadic nature of deontic operators - should produce more correct responses than the conditional formulation in Wason selection task. We tested this assumption by presenting a prescription rule and a prohibition rule in conditional vs. proper deontic formulation. We contrasted this hypothesis with two other hypotheses derived from social contract theory and relevance theory. According to the first theory, a deontic rule expressed in terms of cost-benefit should elicit a cheater detection module, sensible to mental states attributions and thus able to discriminate intentional rule violations from accidental rule violations. We tested this prevision by distinguishing the two types of violations. According to relevance theory, performance in selection task should improve by increasing cognitive effect and decreasing cognitive effort. We tested this prevision by focusing experimental instructions on the rule vs. the action covered by the rule. In study 1, in which 480 undergraduates participated, we tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x rule formulation x type of violation x experimental instructions) between-subjects design. In study 2 – carried out by means of a 2 x 2 (rule formulation x type of violation) between-subjects design - we retested the hypothesis of rule formulation vs. the cheaterdetection hypothesis through a new version of selection task in which intentional vs. accidental rule violations were better discriminated. 240 undergraduates participated in this study. Results corroborate our hypothesis and challenge the contrasting assumptions. However, they show that the conditional formulation of deontic rules produces a lower performance than what is reported in literature.

Keywords: Deontic reasoning; Evolutionary, linguistic, logical, pragmatic factors; Wason selection task

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Authors: Joonas Pääkkönen

Abstract:

In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling.

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Authors: V. Barot, S. McLeod, R. Harrison, A. A. West

Abstract:

Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.

Keywords: Broadcaster, circular buffer, Component-based, distributed manufacturing, remote data propagation.

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Authors: Jindřiška Šedová

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The Czech Republic is a country whose economy has undergone a transformation since 1989. Since joining the EU it has been striving to reduce the differences in its economic standard and the quality of its institutional environment in comparison with developed countries. According to an assessment carried out by the World Bank, the Czech Republic was long classed as a country whose institutional development was seen as problematic. For many years one of the things it was rated most poorly on was its bankruptcy law. The new Insolvency Act, which is a modern law in terms of its treatment of bankruptcy, was first adopted in the Czech Republic in 2006. This law, together with other regulatory measures, offers debtridden Czech economic subjects legal instruments which are well established and in common practice in developed market economies. Since then, analyses performed by the World Bank and the London EBRD have shown that there have been significant steps forward in the quality of Czech bankruptcy law. The Czech Republic still lacks an analytical apparatus which can offer a structured characterisation of the general and specific conditions of Czech company and household debt which is subject to current changes in the global economy. This area has so far not been given the attention it deserves. The lack of research is particularly clear as regards analysis of household debt and householders- ability to settle their debts in a reasonable manner using legal and other state means of regulation. We assume that Czech households have recourse to a modern insolvency law, yet the effective application of this law is hampered by the inconsistencies in the formal and informal institutions involved in resolving debt. This in turn is based on the assumption that this lack of consistency is more marked in cases of personal bankruptcy. Our aim is to identify the symptoms which indicate that for some time the effective application of bankruptcy law in the Czech Republic will be hindered by factors originating in householders- relative inability to identify the risks of falling into debt.

Keywords: bankruptcy law, household debt, consumer bankruptcy, business bankruptcy

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Authors: Karanja Kibicho, Anthony Sayers

Abstract:

Due to adverse pressure gradient along the diverging walls of wide-angled diffusers, the attached flow separates from one wall and remains attached permanently to the other wall in a process called stalling. Stalled diffusers render the whole fluid flow system, in which they are part of, very inefficient. There is then an engineering need to try to understand the whole process of diffuser stall if any meaningful attempts to improve on diffuser efficiency are to be made. In this regard, this paper provides a data bank contribution for the mean flow-field in wide-angled diffusers where the complete velocity and static pressure fields, and pressure recovery data for diffusers in the fully stalled flow regime are experimentally measured. The measurements were carried out at Reynolds numbers between 1.07×105 and 2.14×105 based on inlet hydraulic diameter and centreline velocity for diffusers whose divergence angles were between 30Ôùª and 50Ôùª. Variation of Reynolds number did not significantly affect the velocity and static pressure profiles. The wall static pressure recovery was found to be more sensitive to changes in the Reynolds number. By increasing the velocity from 10 m/s to 20 m/s, the wall static pressure recovery increased by 8.31%. However, as the divergence angle was increased, a similar increase in the Reynolds number resulted in a higher percentage increase in pressure recovery. Experimental results showed that regardless of the wall to which the flow was attached, both the velocity and pressure fields were replicated with discrepancies below 2%.

Keywords: Two-dimensional, wide-angled, diffuser, stall, separated flows, subsonic flows, diffuser flow regimes

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Authors: S. Sundaravalli, M. C. Majumder, G. K. Vijayaraghavan

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The study focuses to investigate the thermal response of delaminations and develop mathematical models using numerical results to obtain the optimum heat requirement and time to identify delaminations in GLARE type of Fibre Metal Laminates (FML) in both reflection mode and through-transmission (TT) mode of step pulsed active thermography (SPAT) method in the type of nondestructive testing and evaluation (NDTE) technique. The influence of applied heat flux and time on various sizes and depth of delaminations in FML is analyzed to investigate the thermal response through numerical simulations. A finite element method (FEM) is applied to simulate SPAT through ANSYS software based on 3D transient heat transfer principle with the assumption of reflection mode and TT mode of observation individually.

The results conclude that the numerical approach based on SPAT in reflection mode is more suitable for analysing smaller size of near-surface delaminations located at the thermal stimulator side and TT mode is more suitable for analysing smaller size of deeper delaminations located far from thermal stimulator side or near thermal detector/Infrared camera side. The mathematical models provide the optimum q and T at the required MRTD to identify unidentified delamination 7 with 25015.0022W/m2 at 2.531sec and delamination 8 with 16663.3356 W/m2 at 1.37857sec in reflection mode. In TT mode, the delamination 1 with 34954W/m2 at 13.0399sec, delamination 2 with 20002.67W/m2 at 1.998sec and delamination 7 with 20010.87 W/m2 at 0.6171sec could be identified.

Keywords: Step pulsed active thermography (SPAT), NDTE, FML, Delaminations, Finite element method.

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: Aerodynamics, flight control, computational fluid dynamics, flapping-wing flight.

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