Search results for: tube based model predictive control

Authors: Saeid Seddegh, Xiaolin Wang, Alan D. Henderson, Dong Chen, Oliver Oims

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The main objective of this research is to study the heat transfer processes and phase change behaviour of a phase change material (PCM) in shell and tube latent heat thermal energy storage (LHTES) systems. The thermal behaviour in a vertical and horizontal shell-and-tube heat energy storage system using a pure thermal conduction model and a combined conduction-convection heat transfer model is compared in this paper. The model is first validated using published experimental data available in literature and then used to study the temperature variation, solid-liquid interface, phase distribution, total melting and solidification time during melting and solidification processes of PCMs. The simulated results show that the combined convection and conduction model can better describe the energy transfer in PCMs during melting process. In contrast, heat transfer by conduction is more significant during the solidification process since the two models show little difference. Also, it was concluded that during the charging process for the horizontal orientation, convective heat transfer has a strong effect on melting of the upper part of the solid PCM and is less significant during melting of the lower half of the solid PCM. However, in the vertical orientation, convective heat transfer is the same active during the entire charging process. In the solidification process, the thermal behavior does not show any difference between horizontal and vertical systems.

Keywords: latent heat thermal energy storage, phase change material, natural convection, melting, shell and tube heat exchanger, melting, solidification

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Authors: Tengqin Han

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Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

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Authors: Hussein M. Maghrabie, M. Attalla, Hany. A. Mohamed, M. Salem, E. Specht

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An experimental investigation is carried out on counter-flow Ranque–Hilsch vortex tube (RHVT). The present work is carried out to study the effect of nozzle aspect ratio, tube length and the inlet pressure (P_i) on the coefficient of performance and energy separation of a RHVT. Further, the effect of moist air with different relative humidity (RH) 40, 60, 80 % is also achieved. The air relative humidity is adjusted using air humidification/dehumidification unit. The experimental study accomplished for number of nozzle N=6, with inner diameter D=7.5 mm., and length of the vortex tube (L) 75, 97.5, and 112.5 mm. The results show that the relative humidity has a significant effect on coefficient of performance and energy separation of a RHVT.

Keywords: COP, counter-flow Ranque–Hilsch vortex tube, energy separation, humid air

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Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

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Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

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Authors: Santhosh Nallapu, G. Radhakrishnamacharya

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A two-fluid model of Herschel-Bulkley fluid flow through tubes of small diameters is studied. It is assumed that the core region consists of Herschel-Bulkley fluid and Newtonian fluid in the peripheral region. The analytical solutions for velocity, flow flux, effective viscosity, core hematocrit and mean hematocrit have been derived and the effects of various relevant parameters on these flow variables have been studied. It has been observed that the effective viscosity and mean hematocrit increase with yield stress, power-law index, hematocrit and tube radius. Further, the core hematocrit decreases with hematocrit and tube radius.

Keywords: two-layered model, non-Newtonian fluid, hematocrit, Fahraeus-Lindqvist effect, plug flow

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Authors: Mahacine Amrani

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This paper aims at reviewing some Moroccan industrial applications of wavelet especially in the dynamic identification of a process model using Haar wavelet mother response. Two recent Moroccan study cases are described using dynamic data originated by a distillation column and an industrial polyethylene process plant. The purpose of the wavelet scheme is to build on-line dynamic models. In both case studies, a comparison is carried out between the Haar wavelet mother response model and a linear difference equation model. Finally it concludes, on the base of the comparison of the process performances and the best responses, which may be useful to create an estimated on-line internal model control and its application towards model-predictive controllers (MPC). All calculations were implemented using AutoSignal Software.

Keywords: process performance, model, wavelets, Haar, Moroccan

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

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Authors: Yana Xiao

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The invention of Triboelectric Nanogenerators (TENGs) provides an effective approach to the sustainable power of energy. Liquid-solid interfaces-based TENGs have been researched in virtue of less friction for harvesting energy from raindrops, rivers, and oceans in the form of water flows. However, TENGs based on droplets have rarely been investigated. In this study, we have proposed a new kind of droplet tube-based TENG (DT-TENG) with free-standing and reformative grating electrodes. Both straight and curved DT-TENGs were designed, fabricated, and evaluated, including straight tubes TENG with 27 electrodes and curved tubes TENG of 25cm radius curvature- at the inclination of 30°, 45° and 60° respectively. Different materials and hydrophobicity treatments for the tubes have also been studied, together with a discussion on the mechanism and applications of DT-TENGs. As different types of liquid discrepant energy performance, this kind of DT-TENG can be potentially used in laboratories to identify liquid or solvent. In addition, a smart fishing float is contrived, which can recognize different levels of movement speeds brought about by different weights and generate corresponding electric signals to remind the angler. The electric generation performance when using a PVC helix tube around a cylinder is similar in straight situations under the inclination of 45° in this experiment. This new structure changes the direction of a water drop or flows without losing kinetic energy, which makes utilizing Helix-Tube-TENG to harvest energy from different building morphologies possible.

Keywords: triboelectric nanogenerator, energy harvest, liquid tribomaterial, structure innovation

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Authors: Praveen Battula

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Any high performance car has the tendency to over steer and Understeer under slippery conditions, An Electronic Stability Control System is needed under these conditions to regulate the steering of the car. It uses Anti-Lock Braking System (ABS) and Traction Control and Wheel Speed Sensor, Steering Angle Sensor, Rotational Speed Sensors to correct the problems. The focus of this paper is to improve the driving dynamics and safety by controlling the forces applied on each wheel. ESC Control the Yaw Stability, traction controls the Roll Stability, where actually the vehicle slip rate and lateral acceleration is controlled. ESC uses differential braking on all four brakes independently to control the vehicle’s motion. A mathematical model is developed in Simulink for the FlexRay based Electronic Stability Control. Vehicle steering is developed using Neuro Fuzzy Logic Controller. 7 Degrees of Freedom Vehicle Model is used as a Plant Model using dSpace autobox. The Performance of the system is assessed using two different road Scenarios, Vehicle Control under standard maneuvering conditions. The entire system is set using Dspace Control Desk. Results are provided by comparison of how a Vehicle with and without Electronic Stability Control which shows an improved performance in control.

Keywords: ESC, flexray, chassis control, steering, neuro fuzzy, vehicle dynamics

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Authors: Chee Wee Gan, Anthony Herr Cheun Ng, Yee Shan Wong, Subbu Venkatraman, Lynne Hsueh Yee Lim

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Otitis media with effusion (OME) is the leading cause of hearing loss in children worldwide. Surgery to insert grommet tube into the eardrum is usually indicated for OME unresponsive to antimicrobial therapy. It is the most common surgery for children. However, current commercially available grommet tubes are non-bioresorbable, not drug-treated, with unpredictable duration of retention on the eardrum to ventilate middle ear. Their functionality is impaired when clogged or chronically infected, requiring additional surgery to remove/reinsert grommet tubes. We envisaged that a novel fully bioresorbable grommet tube with sustained antibiotic release technology could address these drawbacks. In this study, drug-loaded bioresorbable poly(L-lactide-co-ε-caprolactone)(PLC) copolymer grommet tubes were fabricated by microinjection moulding technique. In vitro drug release and degradation model of PLC tubes were studied. Antibacterial property was evaluated by incubating PLC tubes with P. aeruginosa broth. Surface morphology was analyzed using scanning electron microscopy. A preliminary animal study was conducted using guinea pigs as an in vivo model to evaluate PLC tubes with and without drug, with commercial Mini Shah grommet tube as comparison. Our in vitro data showed sustained drug release over 3 months. All PLC tubes revealed exponential degradation profiles over time. Modeling predicted loss of tube functionality in water to be approximately 14 weeks and 17 weeks for PLC with and without drug, respectively. Generally, PLC tubes had less bacteria adherence, which were attributed to the much smoother tube surfaces compared to Mini Shah. Antibiotic from PLC tube further made bacteria adherence on surface negligible. They showed neither inflammation nor otorrhea after 18 weeks post-insertion in the eardrums of guinea pigs, but had demonstrated severe degree of bioresorption. Histology confirmed the new PLC tubes were biocompatible. Analyses on the PLC tubes in the eardrums showed bioresorption profiles close to our in vitro degradation models. The bioresorbable antibiotic-loaded grommet tubes showed good predictability in functionality. The smooth surface and sustained release technology reduced the risk of tube infection. Tube functional duration of 18 weeks allowed sufficient ventilation period to treat OME. Our ongoing studies include modifying the surface properties with protein coating, optimizing the drug dosage in the tubes to enhance their performances, evaluating their functional outcome on hearing after full resoption of grommet tube and healing of eardrums, and developing animal model with OME to further validate our in vitro models.

Keywords: bioresorbable polymer, drug release, grommet tube, guinea pigs, otitis media with effusion

Procedia PDF Downloads 426

Authors: S. H. Chew, Z. X. Eng, K. E. Chuah, T. Y. Lim, H. M. A. Yim

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In recent years, geotextile tube has been widely used in the hydraulic engineering and dewatering industry. To construct a stable containment bund with geotextile tubes, the sand slurry is always the preference infilling material. However, the shortage of sand supply posts a problem in Singapore to adopt this construction method in the actual construction of long containment bund. Hence, utilizing the soft dredged clay or the excavated soft clay as the infilling material of geotextile tubes has a great economic benefit. There are any technical issues with using this soft clayey material as infilling material, especially on the excessive settlement and stability concerns. To minimize the shape deformation and settlement of geotextile tube associated with the use of this soft clay infilling material, a modified innovative infilling material is proposed – lightly cemented soft clay. The preliminary laboratory studies have shown that the dewatering mechanism via geotextile material of the tube skin, and the introduction of cementitious chemical action of the lightly cemented soft clay will accelerate the consolidation and improve the shear strength of infill material. This study aims to extend the study by conducting a pilot test of the geotextile tube filled with lightly cemented clay. This study consists of testing on a series of miniature geo-tubes and two full-size geotextile tube. In the miniature geo-tube tests, a number of small scaled-down size of geotextile tubes were filled with cemented clay (at water content of 150%) with cement content of 0% to 8% (by weight). The shear strength development of the lightly cemented clay under dewatering mechanism was evaluated using a modified in-situ Cone Penetration Test (CPT) at 0 days, 3 days, 7 days and 28 days after the infilling. The undisturbed soil samples of lightly cemented infilled clay were also extracted at 3-days and 7-days for triaxial tests and evaluation of final water content. The results suggested that the geotextile tubes filled with un-cemented soft clay experienced very significant shape change over the days (as control test). However, geotextile mini-tubes filled with lightly cemented clay experienced only marginal shape changed, even that the strength development of this lightly cemented clay inside the tube may not show significant strength gain at the early stage. The shape stability is believed to be due to the confinement effect of the geotextile tube with clay at non-slurry state. Subsequently, a full-scale instrumented geotextile tube filled with lightly cemented clay was performed. The extensive results of strain gauges and pressure transducers installed on this full-size geotextile tube demonstrated a substantial mobilization of tensile forces on the geotextile skin corresponding to the filling activity and the subsequent dewatering stage. Shape change and the in-fill material strength development was also monitored. In summary, the construction of containment bund with geotextile tube filled with lightly cemented clay is found to be technically feasible and stable with the use of the sufficiently strong (i.e. adequate tensile strength) geotextile tube, the adequate control on the dosage of cement content, and suitable water content of infilling soft clay material.

Keywords: cemented clay, containment bund, dewatering, geotextile tube

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Authors: Subodh N. Patel, Abhijit Pusty, Manashi Adhikary, Sandip Bhattacharyya

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The steam superheater (SH) is a coil type heat exchanger which is used to produce superheated steam or to convert the wet steam to dry steam (69.6 kg/cm² and 495°C), generated by a boiler. There were two superheaters in the system, SH I and SH II. SH II is a set of tubes that faces the initial interaction with flue gas at high temperature followed by SH I tubes. After a service life of 2100 hours, a tube in the SH II found to be punctured. Dye penetrant test revealed that out of 50 such tubes, 14 more tubes had severe cracks at a similar location. The failure was investigated in detail. The materials and scale were characterized by optical microscope and advance characterization technique. Scale, observed on fracture surface, was characterized under scanning electron microscope and Raman spectroscopy. Stresses acting on the tubes in working condition were analyzed by finite element method software, ANSYS. Cyclic stresses were observed in the simulation at the same prone location due to restriction in expansion of tubes. Based on scale characterization and stress analysis, it was concluded that the tube failed in thermo-mechanical fatigue. Finally, prevention and control measures were taken to avoid such failure in the future.

Keywords: finite element analysis, oxide scale, superheater tube, thermomechanical fatigue

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Authors: Fuat Korkut, Soner Guler

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The concrete filled steel tube (CFST) columns are commonly used in construction applications such as high-rise buildings and bridges owing to its lots of remarkable benefits. The use of concrete filled steel tube columns provides large areas by reduction in cross-sectional area of columns. The main aim of this study is to examine the axial load capacities of circular high strength concrete filled steel tube columns according to Eurocode 4 (EC4) and Chinese Code (DL/T). The results showed that the predictions of EC4 and Chinese Code DL/T are unsafe for all specimens.

Keywords: concrete-filled steel tube column, axial load capacity, Chinese code, Australian Standard

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

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In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm

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Authors: Ali Motevalli, Shahin Nayyeri Amiri

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Cross-Hole Sonic Logging (CSL) is a common type of Non-Destructive Testing (NDT) method, which is currently used to check the integrity of placed drilled shafts. CSL evaluates the integrity of the concrete inside the cage and between the access tubes based on propagation of ultrasonic waves between two or more access tubes. A number of access tubes are installed inside the reinforcing cage prior to concrete placement as guides for sensors. The access tubes can be PVC or steel galvanized based on ASTM6760. The type of the CSL tubes can affect the axial strength of the drilled shaft. The objective of this study is to compare the amount of axial load capacity of drilled shafts due to using a different type of CSL tubes inside the caging. To achieve this, three (3) large-scale drilled shaft samples were built and tested using a hydraulic actuator at the Florida International University’s (FIU) Titan America Structures and Construction Testing (TASCT) laboratory. During the static load test, load-displacement curves were recorded by the data acquisition system (MegaDAC). Three drilled shaft samples were built to evaluate the effect of the type of the CSL tube on the axial load capacity in drilled shaft foundations.

Keywords: drilled shaft foundations, axial load capacity, cage, PVC, galvanized tube, CSL tube

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Authors: G. Ravindranath, S. Savitha

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This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

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Authors: Emejeamara Francis

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The future of potentials wind energy applications within suburban/urban areas are currently faced with various problems. These include insufficient assessment of urban wind resource, and the effectiveness of commercial gust control solutions as well as unavailability of effective and cheaper valuable tools for scoping the potentials of urban wind applications within built-up environments. In order to achieve effective assessment of the potentials of urban wind installations, an estimation of the total energy that would be available to them were effective control systems to be used, and evaluating the potential power to be generated by the wind system is required. This paper presents a methodology of predicting the power generated by a wind system operating within an urban wind resource. This method was developed by using high temporal resolution wind measurements from eight potential sites within the urban and suburban environment as inputs to a vertical axis wind turbine multiple stream tube model. A relationship between the unsteady performance coefficient obtained from the stream tube model results and turbulence intensity was demonstrated. Hence, an analytical methodology for estimating the unsteady power coefficient at a potential turbine site is proposed. This is combined with analytical models that were developed to predict the wind speed and the excess energy (EEC) available in estimating the potential power generated by wind systems at different heights within a built environment. Estimates of turbulence intensities, wind speed, EEC and turbine performance based on the current methodology allow a more complete assessment of available wind resource and potential urban wind projects. This methodology is applied to four major UK cities namely Leeds, Manchester, London and Edinburgh and the potential to map the turbine performance at different heights within a typical urban city is demonstrated.

Keywords: small-scale wind, turbine power, urban wind energy, turbulence intensity, excess energy content

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Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu

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A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.

Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation

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Authors: Bruk Gebregziabher

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The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

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Authors: Maru R., Singh V. P.

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In this research, analytical study of the flexural strength of Concrete Filled Steel Tube (CFST) beams is carried out based on wide-range finite element models to obtain the better perspective for flexural strength achievement with the use of ABAQUS finite element program. This work adopts concrete damaged plasticity model to get the actual simulation of CFST under bending. To get the decent interaction between concrete and steel, normal and tangential surface interaction provided by ABAQUS is used with hard contact for normal surface interaction and for 0.65 friction coefficient for tangential surface interactions. In this study, rectangular and square CFST beam model cross-sections are adopted with its limits pertained to Eurocode specifications. To get the visualization for flexural strength of CFST beams, total of 74 rectangular CFST beams and 86 square CFST beams are used with four-point bending test setup and the length of the beam model as 1000mm. The grades of concrete and grades of steel are used as 30 MPa & 35MPa and 235 MPa and 275MPa respectively for both sections to get the confinement factor 0.583 to 2.833, steel ratio of 0.069 to 0.236 and length to depth ratio of 4.167 to 16.667. It was found based on this study that flexural strength of CFST beams falls around strain of 0.012. Eurocode provides the results harmonically with finite elemental results. It was also noted for square sections that reduction of steel ratio is not useful as compared to rectangular section although it increases moment capacity up to certain limits because for square sectional area similar to that of rectangular, it possesses lesser depth than rectangular sections. Also It can be said that effect of increment of grade of concrete can be achieved when thicker steel tube is present. It is observed that there is less increment in moment capacity initially but after D/b ratio 1.2, moment capacity of CFST beam rapidly.

Keywords: ABAQUS, CFST beams, flexural strength, four-point bending, rectangular and square sections

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Authors: Bongs Lainjo

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Educational institutions and authorities that are mandated to run education systems in various countries need to implement a curriculum that considers the possibility and existence of elementary school dropouts. This research focuses on elementary school dropout rates and the ability to replicate various predictive models carried out globally on selected Elementary Schools. The study was carried out by comparing the classical case studies in Africa, North America, South America, Asia and Europe. Some of the reasons put forward for children dropping out include the notion of being successful in life without necessarily going through the education process. Such mentality is coupled with a tough curriculum that does not take care of all students. The system has completely led to poor school attendance - truancy which continuously leads to dropouts. In this study, the focus is on developing a model that can systematically be implemented by school administrations to prevent possible dropout scenarios. At the elementary level, especially the lower grades, a child's perception of education can be easily changed so that they focus on the better future that their parents desire. To deal effectively with the elementary school dropout problem, strategies that are put in place need to be studied and predictive models are installed in every educational system with a view to helping prevent an imminent school dropout just before it happens. In a competency-based curriculum that most advanced nations are trying to implement, the education systems have wholesome ideas of learning that reduce the rate of dropout.

Keywords: elementary school, predictive models, machine learning, risk factors, data mining, classifiers, dropout rates, education system, competency-based curriculum

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

Abstract:

Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.

Keywords: control system, hydroponics, machine learning, reinforcement learning

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Authors: Bessaad Taieb, Benbouali Abderrahmen

Abstract:

Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. In this paper, the proposed control method is designed, based on a fuzzy adaptive controller used as a remedy for this problem. For increase the robustness of the vector control and to maintain the performance of the five-phase asynchronous machine despite the presence of disturbances (variation of rotor resistance, rotor inertia variations, sudden variations in the load etc.), by applying the method of behaviour model control (BMC). The results of simulation show that the fuzzy adaptive control provides best performance and has a more robustness as the fuzzy (FLC) and as a conventional (PI) controller.

Keywords: fuzzy adaptive control, behaviour model control, vector control, five-phase asynchronous machine

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Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

Abstract:

Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: additive manufacturing, decision-makings, environmental impact, predictive models

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Authors: Amr AbdelAzim Ali, G. A. Elsheikh, Moutaz M. Hegazy

Abstract:

Reaction wheels (RWs) are generally used as main actuator in the attitude control system (ACS) of spacecraft (SC) for fast orientation and high pointing accuracy. In order to achieve the required accuracy for the RWs model, the main characteristics of the RWs that necessitate analysis during the ACS design phase include: technical features, sequence of operating and RW control logic are included in function (behavior) model. A mathematical model is developed including the various errors source. The errors in control torque including relative, absolute, and error due to time delay. While the errors in angular velocity due to differences between average and real speed, resolution error, loose in installation of angular sensor, and synchronization errors. The friction torque is presented in the model include the different feature of friction phenomena: steady velocity friction, static friction and break-away torque, and frictional lag. The model response is compared with the experimental torque and frequency-response characteristics of tested RWs. Based on the created RW model, some criteria of optimization based control torque allocation problem can be recommended like: avoiding the zero speed crossing, bias angular velocity, or preventing wheel from running on the same angular velocity.

Keywords: friction torque, reaction wheels modeling, software in the loop, spacecraft attitude control

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Authors: Ce Liu, Wei Huo

Abstract:

A nonlinear trajectory tracking controller for quadrotor helicopter based on controlled Lagrangian (CL) method is proposed in this paper. A Lagrangian system with virtual angles as generated coordinates rather than Euler angles is developed. Based on the model, the matching conditions presented by nonlinear partial differential equations are simplified and explicitly solved. Smooth tracking control laws and the range of control parameters are deduced based on the controlled energy of closed-loop system. Besides, a constraint condition for reference accelerations is deduced to identify the trackable reference trajectories by the proposed controller and to ensure the stability of the closed-loop system. The proposed method in this paper does not rely on the division of the quadrotor system, and the design of the control torques does not depend on the thrust as in backstepping or hierarchical control method. Simulations for a quadrotor model demonstrate the feasibility and efficiency of the theoretical results.

Keywords: quadrotor, trajectory tracking control, controlled lagrangians, underactuated system

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

Abstract:

This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Eylem Guzel, Faruk Osmanoglu, Muhammet Kurucu

Abstract:

The concrete filled steel tube (CFST) columns are commonly used in construction applications such as high-rise buildings and bridges owing to its lots of remarkable benefits. The use of concrete-filled steel tube columns provides large areas by reduction in cross-sectional area of columns. The main aim of this study is to examine the axial load capacities of circular high strength concrete-filled steel tube columns according to Eurocode 4 (EC4) and Chinese Code (DL/T). The results showed that the predictions of EC4 and Chinese Code DL/T are unsafe for all specimens.

Keywords: concrete-filled steel tube column, axial load capacity, Chinese code, Australian standard

Procedia PDF Downloads 369