Search results for: gravity gradient inversion algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4688

Search results for: gravity gradient inversion algorithm

4598 Delineating Subsurface Linear Features and Faults Under Sedimentary Cover in the Bahira Basin Using Integrated Gravity and Magnetic Data

Authors: M. Lghoul, N. El Goumi, M. Guernouche

Abstract:

In order to predict the structural and tectonic framework of the Bahira basin and to have a 3D geological modeling of the basin, an integrated multidisciplinary work has been conducted using gravity, magnetic and geological data. The objective of the current study is delineating the subsurfacefeatures, faults, and geological limits, using airborne magnetic and gravity data analysis of the Bahira basin. To achieve our goal, we have applied different enhanced techniques on magnetic and gravity data: power spectral analysis techniques, reduction to pole (RTP), upward continuation, analytical signal, tilt derivative, total horizontal derivative, 3D Euler deconvolutionand source parameter imagining. The major lineaments/faults trend are: NE–SW, NW-SE, ENE–WSW, and WNW–ESE. The 3D Euler deconvolution analysis highlighted a number of fault trend, mainly in the ENE-WSW, WNW-ESE directions. The depth tothe top of the basement sources in the study area ranges between 200 m, in the southern and northern part of the Bahira basin, to 5000 m located in the Eastern part of the basin.

Keywords: magnetic, gravity, structural trend, depth to basement

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4597 Optimal Dynamic Regime for CO Oxidation Reaction Discovered by Policy-Gradient Reinforcement Learning Algorithm

Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.

Abstract:

Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.

Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control

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4596 Quantitative Analysis of the Trade Potential of the United States with Members of the European Union: A Gravity Model Approach

Authors: Zahid Ahmad, Nauman Ali

Abstract:

This study has estimated the trade between USA and individual members of European Union using Gravity Model of Trade as The USA has a complex trade relationship with the European countries consist of a large number of consumers, which make USA dependent on EU for major of its total world trade. However, among the member of EU, the trade potential of USA with individual members of EU is not known. Panel data techniques e.g. Random Effect, Fixed Effect and Pooled Panel have been applied to secondary quantitative data to analyze the Trade between USA and EU. Trade Potential of USA with individual members of EU has been obtained using the ratio of Actual trade of USA with EU members and the trade as predicted by Gravity Model. The Study concluded that the USA has greater trade potential with 16 members of EU, including Croatia, Portugal and United Kingdom on top. On the other hand, Finland, Ireland, and France are the top countries with which the USA has exhaustive trade potential.

Keywords: analytical technique, economic, gravity, international trade, significant

Procedia PDF Downloads 267
4595 Effect of Mineral Ion Addition on Yeast Performance during Very High Gravity Wort Fermentation

Authors: H. O. Udeh, T. E. Kgatla, A. I. O. Jideani

Abstract:

The effect of Zn2+, Mg2+, and Ba2+ on Saccharomyces pastorianus during very high gravity fermentation was evaluated in this study at independent and three variable combinations. Wort gravity of 21oP was prepared from barley malt, hops and water, to which the metal ions were supplemented in their combinations and subsequently pitched. After 96 h of fermentation, high wort fermentability (%F)= 29.53 was obtained in wort medium containing 900:4 ppm Mg2+ + Ba2+. Increased ethanol titre 7.3491 %(v/v) and 7.1313 %(v/v) were obtained in media containing 900:4 ppm Mg2+ + Ba2+ and 12:900 ppm Zn2+ + Mg2+. Decrease %F= 22.54 and ethanol titre 6.1757% (v/v) was recorded in wort medium containing 12:4 ppm Zn2+ + Ba2+. In media containing the individual metal ions, increased %F= 27.94 and %F= 26.03 were obtained in media containing 700 ppm Mg2+ and 2 ppm Ba2+, with increased ethanol yield of 7.8844% (v/v) and 7.6245% (v/v) respectively. Least %F of 11.75 and 10.80, and ethanol titre of 4.99 (%v/v) and 4.80 (%v/v) were obtained for 10 ppm Zn2+ and 4 ppm Ba2+ respectively.

Keywords: ethanol yield, fermentability, mineral ions, yeast stress, very high gravity fermentation

Procedia PDF Downloads 346
4594 Novel Technique for calculating Surface Potential Gradient of Overhead Line Conductors

Authors: Sudip Sudhir Godbole

Abstract:

In transmission line surface potential gradient is a critical design parameter for planning overhead line, as it determines the level of corona loss (CL), radio interference (RI) and audible noise (AN).With increase of transmission line voltage level bulk power transfer is possible, using bundle conductor configuration used, it is more complex to find accurate surface stress in bundle configuration. The majority of existing models for surface gradient calculations are based on analytical methods which restrict their application in simulating complex surface geometry. This paper proposes a novel technique which utilizes both analytical and numerical procedure to predict the surface gradient. One of 400 kV transmission line configurations has been selected as an example to compare the results for different methods. The different strand shapes are a key variable in determining.

Keywords: surface gradient, Maxwell potential coefficient method, market and Mengele’s method, successive images method, charge simulation method, finite element method

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4593 Computer-Aided Detection of Simultaneous Abdominal Organ CT Images by Iterative Watershed Transform

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

Abstract:

Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

Procedia PDF Downloads 413
4592 Progressive Structural Capacity Loss Assessment

Authors: M. Zain, Thaung H. Aung, Naveed Anwar

Abstract:

During the service life, a structure may experience extreme loading conditions. The current study proposes a new methodology that covers the effect of uncertainty involved in gravity loadings on key structural elements of new and complex structures by emphasizing on a very realistic assumption that allows the 'Performance-Based Assessment' to be executed on the structure against the gravity loadings. The methodology does not require the complete removal of an element, instead, it permits the incremental reduction in the capacity of key structural elements and preserves the same stiffness of the member in each case of capacity loss. To demonstrate the application of the proposed methodology, a 13 story complex structure is selected that comprises of a diverse structural configuration. The results ensure the structural integrity against the applied gravity loadings, as well as the effectiveness of the proposed methodology.

Keywords: force-deformation relationship, gravity loading, incremental capacity reduction, multi-linear plastic link element, SAP2000, stiffness

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4591 Seismic Performance Evaluation of Diagrid Components

Authors: Taejin Kim, Heonwoo Lee, Jong-Ho Kim, Dongchul Lee

Abstract:

Recently, there have been various high-rise building projects which reflect unique inspiration from architects to their feature. And it is frequently found that some of these buildings have diagrid structural system. Diagrid system provides engineers many options for structural plan, since it has triangular module so it can form a number of complex shapes. Unlike braced frame systems, diagonal members in diagrid system resist gravity and horizontal loads simultaneously. Correspondingly, diagrid members take roles of both beams and columns, and it is expected that their ductile capacity may depend on the amount of gravity loads. However, not enough studies have been made for this issue so far, which means that there is demand of examination on the seismic behavior of diagrid members under large gravity loads. Therefore, in this study, the ductile capacity of diagrid members was evaluated through analytical and experimental method. Several cases that have different vertical load condition were set up for both approaches to consider the effect of initial compression force due to gravity load. Regarding the result, it was found that buckling in a diagonal member occurs at smaller drift angle when larger gravity load acts on the specimen, which also reduces the amount of energy dissipation. It means that axial stress in a diagonal member reaches critical buckling force early due to the combined axial force from not only horizontal load but also gravity load.

Keywords: buckling, diagrid, ductility, seismic performance

Procedia PDF Downloads 372
4590 Magnetic Navigation of Nanoparticles inside a 3D Carotid Model

Authors: E. G. Karvelas, C. Liosis, A. Theodorakakos, T. E. Karakasidis

Abstract:

Magnetic navigation of the drug inside the human vessels is a very important concept since the drug is delivered to the desired area. Consequently, the quantity of the drug required to reach therapeutic levels is being reduced while the drug concentration at targeted sites is increased. Magnetic navigation of drug agents can be achieved with the use of magnetic nanoparticles where anti-tumor agents are loaded on the surface of the nanoparticles. The magnetic field that is required to navigate the particles inside the human arteries is produced by a magnetic resonance imaging (MRI) device. The main factors which influence the efficiency of the usage of magnetic nanoparticles for biomedical applications in magnetic driving are the size and the magnetization of the biocompatible nanoparticles. In this study, a computational platform for the simulation of the optimal gradient magnetic fields for the navigation of magnetic nanoparticles inside a carotid artery is presented. For the propulsion model of the particles, seven major forces are considered, i.e., the magnetic force from MRIs main magnet static field as well as the magnetic field gradient force from the special propulsion gradient coils. The static field is responsible for the aggregation of nanoparticles, while the magnetic gradient contributes to the navigation of the agglomerates that are formed. Moreover, the contact forces among the aggregated nanoparticles and the wall and the Stokes drag force for each particle are considered, while only spherical particles are used in this study. In addition, gravitational forces due to gravity and the force due to buoyancy are included. Finally, Van der Walls force and Brownian motion are taken into account in the simulation. The OpenFoam platform is used for the calculation of the flow field and the uncoupled equations of particles' motion. To verify the optimal gradient magnetic fields, a covariance matrix adaptation evolution strategy (CMAES) is used in order to navigate the particles into the desired area. A desired trajectory is inserted into the computational geometry, which the particles are going to be navigated in. Initially, the CMAES optimization strategy provides the OpenFOAM program with random values of the gradient magnetic field. At the end of each simulation, the computational platform evaluates the distance between the particles and the desired trajectory. The present model can simulate the motion of particles when they are navigated by the magnetic field that is produced by the MRI device. Under the influence of fluid flow, the model investigates the effect of different gradient magnetic fields in order to minimize the distance of particles from the desired trajectory. In addition, the platform can navigate the particles into the desired trajectory with an efficiency between 80-90%. On the other hand, a small number of particles are stuck to the walls and remains there for the rest of the simulation.

Keywords: artery, drug, nanoparticles, navigation

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4589 Determination of Aquifer Geometry Using Geophysical Methods: A Case Study from Sidi Bouzid Basin, Central Tunisia

Authors: Dhekra Khazri, Hakim Gabtni

Abstract:

Because of Sidi Bouzid water table overexploitation, this study aims at integrating geophysical methods to determinate aquifers geometry assessing their geological situation and geophysical characteristics. However in highly tectonic zones controlled by Atlassic structural features with NE-SW major directions (central Tunisia), Bouguer gravimetric responses of some areas can be as much dominated by the regional structural tendency, as being non-identified or either defectively interpreted such as the case of Sidi Bouzid basin. This issue required a residual gravity anomaly elaboration isolating the Sidi Bouzid basin gravity response ranging between -8 and -14 mGal and crucial for its aquifers geometry characterization. Several gravity techniques helped constructing the Sidi Bouzid basin's residual gravity anomaly, such as Upwards continuation compared to polynomial regression trends and power spectrum analysis detecting deep basement sources at (3km), intermediate (2km) and shallow sources (1km). A 3D Euler Deconvolution was also performed detecting deepest accidents trending NE-SW, N-S and E-W with depth values reaching 5500 m and delineating the main outcropping structures of the study area. Further gravity treatments highlighted the subsurface geometry and structural features of Sidi Bouzid basin over Horizontal and vertical gradient, and also filters based on them such as Tilt angle and Source Edge detector locating rooted edges or peaks from potential field data detecting a new E-W lineament compartmentalizing the Sidi Bouzid gutter into two unequally residual anomaly and subsiding domains. This subsurface morphology is also detected by the used 2D seismic reflection sections defining the Sidi Bouzid basin as a deep gutter within a tectonic set of negative flower structures, and collapsed and tilted blocks. Furthermore, these structural features were confirmed by forward gravity modeling process over several modeled residual gravity profiles crossing the main area. Sidi Bouzid basin (central Tunisia) is also of a big interest cause of the unknown total thickness and the undefined substratum of its siliciclastic Tertiary package, and its aquifers unbounded structural subsurface features and deep accidents. The Combination of geological, hydrogeological and geophysical methods is then of an ultimate need. Therefore, a geophysical methods integration based on gravity survey supporting available seismic data through forward gravity modeling, enhanced lateral and vertical extent definition of the basin's complex sedimentary fill via 3D gravity models, improved depth estimation by a depth to basement modeling approach, and provided 3D isochronous seismic mapping visualization of the basin's Tertiary complex refining its geostructural schema. A subsurface basin geomorphology mapping, over an ultimate matching between the basin's residual gravity map and the calculated theoretical signature map, was also displayed over the modeled residual gravity profiles. An ultimate multidisciplinary geophysical study of the Sidi Bouzid basin aquifers can be accomplished via an aeromagnetic survey and a 4D Microgravity reservoir monitoring offering temporal tracking of the target aquifer's subsurface fluid dynamics enhancing and rationalizing future groundwater exploitation in this arid area of central Tunisia.

Keywords: aquifer geometry, geophysics, 3D gravity modeling, improved depths, source edge detector

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4588 Movement of Metallic Inclusions in the Volume of Synthetic Diamonds at High Pressure and High Temperature in the Temperature Gradient Field

Authors: P. I. Yachevskaya, S. A. Terentiev, M. S. Kuznetsov

Abstract:

Several synthetic HPHT diamonds with metal inclusions have been studied. To have possibility of investigate the movement and transformation of the inclusions in the volume of the diamond the samples parallele-piped like shape has been made out of diamond crystals. The calculated value of temperature gradient in the samples of diamond which was placed in high-pressure cell was about 5-10 grad/mm. Duration of the experiments was in range 2-16 hours. All samples were treated several times. It has been found that the volume (dimensions) of inclusions, temperature, temperature gradient and the crystallographic orientation of the samples in the temperature field affects the movement speed of inclusions. Maximum speed of inclusions’ movement reached a value 150 µm/h.

Keywords: diamond, inclusions, temperature gradient, HPHT

Procedia PDF Downloads 468
4587 GIS-Based Topographical Network for Minimum “Exertion” Routing

Authors: Katherine Carl Payne, Moshe Dror

Abstract:

The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

Procedia PDF Downloads 518
4586 Performance Investigation of UAV Attitude Control Based on Modified PI-D and Nonlinear Dynamic Inversion

Authors: Ebrahim Hassan Kapeel, Ahmed Mohsen Kamel, Hossan Hendy, Yehia Z. Elhalwagy

Abstract:

Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control lawisdesigned for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.

Keywords: UAV dynamic model, attitude control, nonlinear PID, dynamic inversion

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4585 Generalized Uncertainty Principle Modified Hawking Radiation in Bumblebee Gravity

Authors: Sara Kanzi, Izzet Sakalli

Abstract:

The effect of Lorentz symmetry breaking (LSB) on the Hawking radiation of Schwarzschild-like black hole found in the bumblebee gravity model (SBHBGM) is studied in the framework of quantum gravity. To this end, we consider Hawking radiation spin-0 (bosons) and spin-12particles (fermions), which go in and out through the event horizon of the SBHBGM. We use the modified Klein-Gordon and Dirac equations, which are obtained from the generalized uncertainty principle (GUP) to show how Hawking radiation is affected by the GUP and LSB. In particular, we reveal that independent of the spin of the emitted particles, GUP causes a change in the Hawking temperature of the SBHBGM. Furthermore, we compute the semi-analytic greybody factors (for both bosons and fermions) of the SBHBGM. Thus, we reveal that LSB is effective on the greybody factor of the SBHBGM such that its redundancy decreases the value of the greybody factor. Our findings are graphically depicted.

Keywords: bumblebee gravity model, Hawking radiation, generalized uncertainty principle, Lorentz symmetry breaking

Procedia PDF Downloads 105
4584 Design of Geochemical Maps of Industrial City Using Gradient Boosting and Geographic Information System

Authors: Ruslan Safarov, Zhanat Shomanova, Yuri Nossenko, Zhandos Mussayev, Ayana Baltabek

Abstract:

Geochemical maps of distribution of polluting elements V, Cr, Mn, Co, Ni, Cu, Zn, Mo, Cd, Pb on the territory of the Pavlodar city (Kazakhstan), which is an industrial hub were designed. The samples of soil were taken from 100 locations. Elemental analysis has been performed using XRF. The obtained data was used for training of the computational model with gradient boosting algorithm. The optimal parameters of model as well as the loss function were selected. The computational model was used for prediction of polluting elements concentration for 1000 evenly distributed points. Based on predicted data geochemical maps were created. Additionally, the total pollution index Zc was calculated for every from 1000 point. The spatial distribution of the Zc index was visualized using GIS (QGIS). It was calculated that the maximum coverage area of the territory of the Pavlodar city belongs to the moderately hazardous category (89.7%). The visualization of the obtained data allowed us to conclude that the main source of contamination goes from the industrial zones where the strategic metallurgical and refining plants are placed.

Keywords: Pavlodar, geochemical map, gradient boosting, CatBoost, QGIS, spatial distribution, heavy metals

Procedia PDF Downloads 54
4583 Co-Evolutionary Fruit Fly Optimization Algorithm and Firefly Algorithm for Solving Unconstrained Optimization Problems

Authors: R. M. Rizk-Allah

Abstract:

This paper presents co-evolutionary fruit fly optimization algorithm based on firefly algorithm (CFOA-FA) for solving unconstrained optimization problems. The proposed algorithm integrates the merits of fruit fly optimization algorithm (FOA), firefly algorithm (FA) and elite strategy to refine the performance of classical FOA. Moreover, co-evolutionary mechanism is performed by applying FA procedures to ensure the diversity of the swarm. Finally, the proposed algorithm CFOA- FA is tested on several benchmark problems from the usual literature and the numerical results have demonstrated the superiority of the proposed algorithm for finding the global optimal solution.

Keywords: firefly algorithm, fruit fly optimization algorithm, unconstrained optimization problems

Procedia PDF Downloads 506
4582 Identification of Wiener Model Using Iterative Schemes

Authors: Vikram Saini, Lillie Dewan

Abstract:

This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

Procedia PDF Downloads 366
4581 Performance Investigation of Unmanned Aerial Vehicles Attitude Control Based on Modified PI-D and Nonlinear Dynamic Inversion

Authors: Ebrahim H. Kapeel, Ahmed M. Kamel, Hossam Hendy, Yehia Z. Elhalwagy

Abstract:

Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control law is designed for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.

Keywords: attitude control, nonlinear PID, dynamic inversion

Procedia PDF Downloads 74
4580 Derivation of Bathymetry from High-Resolution Satellite Images: Comparison of Empirical Methods through Geographical Error Analysis

Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

Abstract:

Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

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4579 A Hybrid System of Hidden Markov Models and Recurrent Neural Networks for Learning Deterministic Finite State Automata

Authors: Pavan K. Rallabandi, Kailash C. Patidar

Abstract:

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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4578 A Simple Heat and Mass Transfer Model for Salt Gradient Solar Ponds

Authors: Safwan Kanan, Jonathan Dewsbury, Gregory Lane-Serff

Abstract:

A salinity gradient solar pond is a free energy source system for collecting, converting and storing solar energy as heat. In this paper, the principles of solar pond are explained. A mathematical model is developed to describe and simulate heat and mass transfer behavior of salinity gradient solar pond. Matlab codes are programmed to solve the one dimensional finite difference method for heat and mass transfer equations. Temperature profiles and concentration distributions are calculated. The numerical results are validated with experimental data and the results are found to be in good agreement.

Keywords: finite difference method, salt-gradient solar-pond, solar energy, transient heat and mass transfer

Procedia PDF Downloads 340
4577 Kriging-Based Global Optimization Method for Bluff Body Drag Reduction

Authors: Bingxi Huang, Yiqing Li, Marek Morzynski, Bernd R. Noack

Abstract:

We propose a Kriging-based global optimization method for active flow control with multiple actuation parameters. This method is designed to converge quickly and avoid getting trapped into local minima. We follow the model-free explorative gradient method (EGM) to alternate between explorative and exploitive steps. This facilitates a convergence similar to a gradient-based method and the parallel exploration of potentially better minima. In contrast to EGM, both kinds of steps are performed with Kriging surrogate model from the available data. The explorative step maximizes the expected improvement, i.e., favors regions of large uncertainty. The exploitive step identifies the best location of the cost function from the Kriging surrogate model for a subsequent weight-biased linear-gradient descent search method. To verify the effectiveness and robustness of the improved Kriging-based optimization method, we have examined several comparative test problems of varying dimensions with limited evaluation budgets. The results show that the proposed algorithm significantly outperforms some model-free optimization algorithms like genetic algorithm and differential evolution algorithm with a quicker convergence for a given budget. We have also performed direct numerical simulations of the fluidic pinball (N. Deng et al. 2020 J. Fluid Mech.) on three circular cylinders in equilateral-triangular arrangement immersed in an incoming flow at Re=100. The optimal cylinder rotations lead to 44.0% net drag power saving with 85.8% drag reduction and 41.8% actuation power. The optimal results for active flow control based on this configuration have achieved boat-tailing mechanism by employing Coanda forcing and wake stabilization by delaying separation and minimizing the wake region.

Keywords: direct numerical simulations, flow control, kriging, stochastic optimization, wake stabilization

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4576 Improving the Efficiency of a High Pressure Turbine by Using Non-Axisymmetric Endwall: A Comparison of Two Optimization Algorithms

Authors: Abdul Rehman, Bo Liu

Abstract:

Axial flow turbines are commonly designed with high loads that generate strong secondary flows and result in high secondary losses. These losses contribute to almost 30% to 50% of the total losses. Non-axisymmetric endwall profiling is one of the passive control technique to reduce the secondary flow loss. In this paper, the non-axisymmetric endwall profile construction and optimization for the stator endwalls are presented to improve the efficiency of a high pressure turbine. The commercial code NUMECA Fine/ Design3D coupled with Fine/Turbo was used for the numerical investigation, design of experiments and the optimization. All the flow simulations were conducted by using steady RANS and Spalart-Allmaras as a turbulence model. The non-axisymmetric endwalls of stator hub and shroud were created by using the perturbation law based on Bezier Curves. Each cut having multiple control points was supposed to be created along the virtual streamlines in the blade channel. For the design of experiments, each sample was arbitrarily generated based on values automatically chosen for the control points defined during parameterization. The Optimization was achieved by using two algorithms i.e. the stochastic algorithm and gradient-based algorithm. For the stochastic algorithm, a genetic algorithm based on the artificial neural network was used as an optimization method in order to achieve the global optimum. The evaluation of the successive design iterations was performed using artificial neural network prior to the flow solver. For the second case, the conjugate gradient algorithm with a three dimensional CFD flow solver was used to systematically vary a free-form parameterization of the endwall. This method is efficient and less time to consume as it requires derivative information of the objective function. The objective function was to maximize the isentropic efficiency of the turbine by keeping the mass flow rate as constant. The performance was quantified by using a multi-objective function. Other than these two classifications of the optimization methods, there were four optimizations cases i.e. the hub only, the shroud only, and the combination of hub and shroud. For the fourth case, the shroud endwall was optimized by using the optimized hub endwall geometry. The hub optimization resulted in an increase in the efficiency due to more homogenous inlet conditions for the rotor. The adverse pressure gradient was reduced but the total pressure loss in the vicinity of the hub was increased. The shroud optimization resulted in an increase in efficiency, total pressure loss and entropy were reduced. The combination of hub and shroud did not show overwhelming results which were achieved for the individual cases of the hub and the shroud. This may be caused by fact that there were too many control variables. The fourth case of optimization showed the best result because optimized hub was used as an initial geometry to optimize the shroud. The efficiency was increased more than the individual cases of optimization with a mass flow rate equal to the baseline design of the turbine. The results of artificial neural network and conjugate gradient method were compared.

Keywords: artificial neural network, axial turbine, conjugate gradient method, non-axisymmetric endwall, optimization

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4575 Effect of Gravity on the Controlled Cooling of a Steel Block by Impinging Water Jets

Authors: E.K.K. Agyeman, P. Mousseau, A. Sarda, D. Edelin

Abstract:

The uniform and controlled cooling of hot metals by the circulation of water in canals remains a challenge due to the phase change of the water and the high heat fluxes associated with the phase change. This is because, during the cooling process, the phases are not uniformly distributed along the canals with the liquid phase dominating at the entrances of the canals and the gaseous phase dominating towards the exits. The difference in thermal properties between both phases leads to a heterogeneous temperature distribution in the part being cooled. Slowing down the cooling process is also a challenge due to the high heat fluxes associated with the phase change of water. This study investigates the use of multiple water jets for the controlled and homogenous cooling of hot metal parts and the effect of gravity on the effectiveness of the cooling process with a potential application in the cooling of composite forming moulds. A hole is bored at the centre of a steel block along its length. The jets are generated from the holes of a perforated steel pipe which is placed along the centre of the hole bored in the steel block. The evolution of the temperature with respect to time on the external surface of the steel block is measured simultaneously by thermocouples and an infrared camera. Different jet positions are tested in order to identify the jet placement configuration that ensures the most homogenous cooling of the block while the cooling speed is controlled by an intermittent impingement of the jets. In order to study the effect of gravity on the cooling process, a scenario where the jets are oriented in the opposite direction to that of gravity is compared to one where the jets are aligned in the same direction as gravity. It’s observed that orienting the jets in the direction of gravity reduces the effectiveness of the cooling process on the face of the block facing the impinging jets. This is due to the formation of a deeper pool of water due to the effect gravity and of the curved surface of the canal. This deeper pool of water influences the boiling regime characterized by a slower bubble evacuation when compared to the scenario where the jets are opposed to gravity.

Keywords: cooling speed, gravity, homogenous cooling, jet impingement

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4574 Subspace Rotation Algorithm for Implementing Restricted Hopfield Network as an Auto-Associative Memory

Authors: Ci Lin, Tet Yeap, Iluju Kiringa

Abstract:

This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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4573 A Cellular Automaton Model Examining the Effects of Oxygen, Hydrogen Ions, and Lactate on Early Tumour Growth

Authors: Maymona Al-Husari, Craig Murdoch, Steven Webb

Abstract:

Some tumors are known to exhibit an extracellular pH that is more acidic than the intracellular, creating a 'reversed pH gradient' across the cell membrane and this has been shown to affect their invasive and metastatic potential. Tumour hypoxia also plays an important role in tumour development and has been directly linked to both tumour morphology and aggressiveness. In this paper, we present a hybrid mathematical model of intracellular pH regulation that examines the effect of oxygen and pH on tumour growth and morphology. In particular, we investigate the impact of pH regulatory mechanisms on the cellular pH gradient and tumour morphology. Analysis of the model shows that: low activity of the Na+/H+ exchanger or a high rate of anaerobic glycolysis can give rise to a 'fingering' tumour morphology; and a high activity of the lactate/H+ symporter can result in a reversed transmembrane pH gradient across a large portion of the tumour mass. Also, the reversed pH gradient is spatially heterogenous within the tumour, with a normal pH gradient observed within an intermediate growth layer, that is the layer between the proliferative inner and outermost layer of the tumour.

Keywords: acidic pH, cellular automaton, ebola, tumour growth

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4572 Local Radial Basis Functions for Helmholtz Equation in Seismic Inversion

Authors: Hebert Montegranario, Mauricio Londoño

Abstract:

Solutions of Helmholtz equation are essential in seismic imaging methods like full wave inversion, which needs to solve many times the wave equation. Traditional methods like Finite Element Method (FEM) or Finite Differences (FD) have sparse matrices but may suffer the so called pollution effect in the numerical solutions of Helmholtz equation for large values of the wave number. On the other side, global radial basis functions have a better accuracy but produce full matrices that become unstable. In this research we combine the virtues of both approaches to find numerical solutions of Helmholtz equation, by applying a meshless method that produce sparse matrices by local radial basis functions. We solve the equation with absorbing boundary conditions of the kind Clayton-Enquist and PML (Perfect Matched Layers) and compared with results in standard literature, showing a promising performance by tackling both the pollution effect and matrix instability.

Keywords: Helmholtz equation, meshless methods, seismic imaging, wavefield inversion

Procedia PDF Downloads 516
4571 The Inversion of Helical Twist Sense in Liquid Crystal by Spectroscopy Methods

Authors: Anna Drzewicz, Marzena Tykarska

Abstract:

The chiral liquid crystal phases form the helicoidal structure, which is characterized by the helical pitch and the helical twist sense. In anticlinic smectic phase with antiferroelectric properties three types of helix temperature dependence have been obtained: increased helical pitch with temperature and right-handed helix, decreased helical pitch with temperature and left-handed helix and the inversion of both. The change of helical twist sense may be observed during the transition from one liquid crystal phase to another or within one phase for the same substance. According to Gray and McDonnell theory, the helical handedness depends on the absolute configuration of the assymetric carbon atom and its position related to the rigid core of the molecule. However, this theory does not explain the inversion of helical twist sense phenomenon. It is supposed, that it may be caused by the presence of different conformers with opposite handendess, which concentration may change with temperature. In this work, the inversion of helical twist sense in the chiral liquid crystals differing in the length of alkyl chain, in the substitution the benzene ring by fluorine atoms and in the type of helix handedness was tested by vibrational spectroscopy (infrared and raman spectroscopy) and by nuclear magnetic resonance spectroscopy. The results obtained from the vibrational spectroscopy confirm the presence of different conformers. Moreover, the analysis of nuclear magnetic resonance spectra is very useful to check, on which structural fragments the change of conformations are important for the change of helical twist sense.

Keywords: helical twist sense, liquid crystals, nuclear magnetic resonance spectroscopy, vibrational spectroscopy

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4570 The Gravitational Impact of the Sun and the Moon on Heavy Mineral Deposits and Dust Particles in Low Gravity Regions of the Earth

Authors: T. B. Karu Jayasundara

Abstract:

The Earth’s gravity is not uniform. The satellite imageries of the Earth’s surface from NASA reveal a number of different gravity anomaly regions all over the globe. When the moon rotates around the earth, its gravity has a major physical influence on a number of regions on the earth. This physical change can be seen by the tides. The tides make sea levels high and low in coastal regions. During high tide, the gravitational force of the Moon pulls the Earth’s gravity so that the total gravitational intensity of Earth is reduced; it is further reduced in the low gravity regions of Earth. This reduction in gravity helps keep the suspended particles such as dust in the atmosphere, sand grains in the sea water for longer. Dramatic differences can be seen from the floating dust in the low gravity regions when compared with other regions. The above phenomena can be demonstrated from experiments. The experiments have to be done in high and low gravity regions of the earth during high and low tide, which will assist in comparing the final results. One of the experiments that can be done is by using a water filled cylinder about 80 cm tall, a few particles, which have the same density and same diameter (about 1 mm) and a stop watch. The selected particles were dropped from the surface of the water in the cylinder and the time taken for the particles to reach the bottom of the cylinder was measured using the stop watch. The times of high and low tide charts can be obtained from the regional government authorities. This concept is demonstrated by the particle drop times taken at high and low tides. The result of the experiment shows that the particle settlement time is less in low tide and high in high tide. The experiment for dust particles in air can be collected on filters, which are cellulose ester membranes and using a vacuum pump. The dust on filters can be used to make slides according to the NOHSC method. Counting the dust particles on the slides can be done using a phase contrast microscope. The results show that the concentration of dust is high at high tide and low in low tide. As a result of the high tides, a high concentration of heavy minerals deposit on placer deposits and dust particles retain in the atmosphere for longer in low gravity regions. These conditions are remarkably exhibited in the lowest low gravity region of the earth, mainly in the regions of India, Sri Lanka and in the middle part of the Indian Ocean. The biggest heavy mineral placer deposits are found in coastal regions of India and Sri Lanka and heavy dust particles are found in the atmosphere of India, particularly in the Delhi region.

Keywords: gravity, minerals, tides, moon, costal, atmosphere

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4569 Comparison between XGBoost, LightGBM and CatBoost Using a Home Credit Dataset

Authors: Essam Al Daoud

Abstract:

Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: gradient boosting, XGBoost, LightGBM, CatBoost, home credit

Procedia PDF Downloads 131