Search results for: predict
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2369

Search results for: predict

1049 Experimental Validation of a Mathematical Model for Sizing End-of-Production-Line Test Benches for Electric Motors of Electric Vehicle

Authors: Emiliano Lustrissimi, Bonifacio Bianco, Sebastiano Caravaggi, Antonio Rosato

Abstract:

A mathematical framework has been designed to enhance the configuration of an end-of-production-line (EOL) test bench. This system can be used to assess the performance of electric motors or axles intended for electric vehicles. The model has been developed to predict the behaviour of EOL test benches and electric motors/axles under various boundary conditions, eliminating the need for extensive physical testing and reducing the corresponding power consumption. The suggested model is versatile, capable of being utilized across various types of electric motors or axles, and adaptable to accommodate varying power ratings of electric motors or axles. The maximum performance to be guaranteed by the EMs according to the car maker's specifications are taken as inputs in the model. Then, the required performance of each main EOL test bench component is calculated, and the corresponding systems available on the market are selected based on manufacturers’ catalogues. In this study, an EOL test bench has been designed according to the proposed model outputs for testing a low-power (about 22 kW) electric axle. The performance of the designed EOL test bench has been measured and used to validate the proposed model and assess both the consistency of the constraints as well as the accuracy of predictions in terms of electric demands. The comparison between experimental and predicted data exhibited a reasonable agreement, allowing to demonstrate that, despite some discrepancies, the model gives an accurate representation of the EOL test benches' performance.

Keywords: electric motors, electric vehicles, end-of-production-line test bench, mathematical model, field tests

Procedia PDF Downloads 34
1048 Phase Behavior Modelling of Libyan Near-Critical Gas-Condensate Field

Authors: M. Khazam, M. Altawil, A. Eljabri

Abstract:

Fluid properties in states near a vapor-liquid critical region are the most difficult to measure and to predict with EoS models. The principal model difficulty is that near-critical property variations do not follow the same mathematics as at conditions far away from the critical region. Libyan NC98 field in Sirte basin is a typical example of near critical fluid characterized by high initial condensate gas ratio (CGR) greater than 160 bbl/MMscf and maximum liquid drop-out of 25%. The objective of this paper is to model NC98 phase behavior with the proper selection of EoS parameters and also to model reservoir depletion versus gas cycling option using measured PVT data and EoS Models. The outcomes of our study revealed that, for accurate gas and condensate recovery forecast during depletion, the most important PVT data to match are the gas phase Z-factor and C7+ fraction as functions of pressure. Reasonable match, within -3% error, was achieved for ultimate condensate recovery at abandonment pressure of 1500 psia. The smooth transition from gas-condensate to volatile oil was fairly simulated by the tuned PR-EoS. The predicted GOC was approximately at 14,380 ftss. The optimum gas cycling scheme, in order to maximize condensate recovery, should not be performed at pressures less than 5700 psia. The contribution of condensate vaporization for such field is marginal, within 8% to 14%, compared to gas-gas miscible displacement. Therefore, it is always recommended, if gas recycle scheme to be considered for this field, to start it at the early stage of field development.

Keywords: EoS models, gas-condensate, gas cycling, near critical fluid

Procedia PDF Downloads 307
1047 Nuclear Characteristics of a Heterogeneous Thorium-Based Fuel Design Aimed at Increasing Fuel Cycle Length of a Typical PWR

Authors: Hendrik Bernard Van Der Walt, Frik Van Niekerk

Abstract:

Heterogeneous thorium-based fuels have been proposed as an alternative for conventional reactor fuels and many studies have shown promising results. Fuel cycle characteristics still have to be explored in detail. This study investigates the use of a novel thorium-based fuel design aimed at increasing fuel cycle length of a typical PWR with an explicit focus on thorium- uranium content, neutron spectrum, flux considerations and neutron economy.As nuclear reactions are highly dependent on reactor flux and material matrix, analytical and numerical calculations have been completed to predict the behaviour of the proposed nuclear fuel. The proposed design utilizes various ratios of thorium oxide and uranium oxide pellets within fuel pins, divided into heterogeneous sections of specified length. This design renders multiple regions with unique characteristics. The goal of this study is to determine and optimally utilize these characteristics. Proliferation considerations result in the need for denaturing of heterogeneous regions, which renders more unique characteristics, these aspects were examined in this study. Finally, the use of fertile thorium to emulate a burnable poison for managing excess BOL reactivity has been investigated, as well as an option for flux shaping in a typical PWR.

Keywords: nuclear fuel, nuclear characteristics, nuclear fuel cycle, thorium-based fuel, heterogeneous design

Procedia PDF Downloads 123
1046 A Finite Element Based Predictive Stone Lofting Simulation Methodology for Automotive Vehicles

Authors: Gaurav Bisht, Rahul Rathnakumar, Ravikumar Duggirala

Abstract:

Predictive simulations are one of the key focus areas in safety-critical industries such as aerospace and high-performance automotive engineering. The stone-chipping study is one such effort taken up by the industry to predict and evaluate the damage caused due to gravel impact on vehicles. This paper describes a finite elements based method that can simulate the ejection of gravel chips from a vehicle tire. The FE simulations were used to obtain the initial ejection velocity of the stones for various driving conditions using a computational contact mechanics approach. To verify the accuracy of the tire model, several parametric studies were conducted. The FE simulations resulted in stone loft velocities ranging from 0–8 m/s, regardless of tire speed. The stress on the tire at the instant of initial contact with the stone increased linearly with vehicle speed. Mesh convergence studies indicated that a highly resolved tire mesh tends to result in better momentum transfer between the tire and the stone. A fine tire mesh also showed a linearly increasing relationship between the tire forward speed and stone lofting speed, which was not observed in coarser meshes. However, it also highlighted a potential challenge, in that the ejection velocity vector of the stone seemed to be sensitive to the mesh, owing to the FE-based contact mechanical formulation of the problem.

Keywords: abaqus, contact mechanics, foreign object debris, stone chipping

Procedia PDF Downloads 252
1045 Semi-Analytic Method in Fast Evaluation of Thermal Management Solution in Energy Storage System

Authors: Ya Lv

Abstract:

This article presents the application of the semi-analytic method (SAM) in the thermal management solution (TMS) of the energy storage system (ESS). The TMS studied in this work is fluid cooling. In fluid cooling, both effective heat conduction and heat convection are indispensable due to the heat transfer from solid to fluid. Correspondingly, an efficient TMS requires a design investigation of the following parameters: fluid inlet temperature, ESS initial temperature, fluid flow rate, working c rate, continuous working time, and materials properties. Their variation induces a change of thermal performance in the battery module, which is usually evaluated by numerical simulation. Compared to complicated computation resources and long computation time in simulation, the SAM is developed in this article to predict the thermal influence within a few seconds. In SAM, a fast prediction model is reckoned by combining numerical simulation with theoretical/empirical equations. The SAM can explore the thermal effect of boundary parameters in both steady-state and transient heat transfer scenarios within a short time. Therefore, the SAM developed in this work can simplify the design cycle of TMS and inspire more possibilities in TMS design.

Keywords: semi-analytic method, fast prediction model, thermal influence of boundary parameters, energy storage system

Procedia PDF Downloads 134
1044 Enhancements to the Coupled Hydro-Mechanical Hypoplastic Model for Unsaturated Soils

Authors: Shanujah Mathuranayagam, William Fuentes, Samanthika Liyanapathirana

Abstract:

This paper introduces an enhanced version of the coupled hydro-mechanical hypoplastic model. The model is able to simulate volumetric collapse upon wetting and incorporates suction effects on stiffness and strength. Its mechanical constitutive equation links Bishop’s effective stress with strain and suction, featuring a normal consolidation line (NCL) with a compression index (λ) presenting a non-linear dependency with the degree of saturation. The Bulk modulus has been modified to ensure that under rapid volumetric collapse, the stress state remains at the NCL. The coupled model comprises eighteen parameters, with nine for the hydraulic component and nine for the mechanical component. Hydraulic parameters are calibrated with the use of water retention curves (IWRC) across varied soil densities, while mechanical parameters undergo calibration using isotropic and triaxial tests on both unsaturated and saturated samples. The model's performance is analyzed through the back-calculation of two experimental studies: (i) wetting under different vertical stresses for Lower Cromer Till and (ii) isotropic loading and triaxial loading for undisturbed loess. The results confirm that the proposed model is able to predict the hydro-mechanical behavior of unsaturated soils.

Keywords: hypoplastic model, volumetric collapse, normal consolidation line, compression index (λ), degree of saturation, soil suction

Procedia PDF Downloads 44
1043 Wave Velocity-Rock Property Relationships in Shallow Marine Libyan Carbonate Reservoir

Authors: Tarek S. Duzan, Abdulaziz F. Ettir

Abstract:

Wave velocities, Core and Log petrophysical data were collected from recently drilled four new wells scattered through-out the Dahra/Jofra (PL-5) Reservoir. The collected data were analyzed for the relationships of Wave Velocities with rock property such as Porosity, permeability and Bulk Density. Lots of Literature review reveals a number of differing results and conclusions regarding wave velocities (Compressional Waves (Vp) and Shear Waves (Vs)) versus rock petrophysical property relationships, especially in carbonate reservoirs. In this paper, we focused on the relationships between wave velocities (Vp , Vs) and the ratio Vp/Vs with rock properties for shallow marine libyan carbonate reservoir (Real Case). Upon data analysis, a relationship between petrophysical properties and wave velocities (Vp, Vs) and the ratio Vp/Vs has been found. Porosity and bulk density properties have shown exponential relationship with wave velocities, while permeability has shown a power relationship in the interested zone. It is also clear that wave velocities (Vp , Vs) seems to be a good indicator for the lithology change with true vertical depth. Therefore, it is highly recommended to use the output relationships to predict porosity, bulk density and permeability of the similar reservoir type utilizing the most recent seismic data.

Keywords: conventional core analysis (porosity, permeability bulk density) data, VS wave and P-wave velocities, shallow carbonate reservoir in D/J field

Procedia PDF Downloads 312
1042 Combating Malaria: A Drug Discovery Approach Using Thiazole Derivatives Against Prolific Parasite Enzyme PfPKG

Authors: Hari Bezwada, Michelle Cheon, Ryan Divan, Hannah Escritor, Michelle Kagramian, Isha Korgaonkar, Maya MacAdams, Udgita Pamidigantam, Richard Pilny, Eleanor Race, Angadh Singh, Nathan Zhang, LeeAnn Nguyen, Fina Liotta

Abstract:

Malaria is a deadly disease caused by the Plasmodium parasite, which continues to develop resistance to current antimalarial drugs. In this research project, the effectiveness of numerous thiazole derivatives was explored in inhibiting the PfPKG, a crucial part of the Plasmodium life cycle. This study involved the synthesis of six thiazole-derived amides to inhibit the PfPKG pathway. Nuclear Magnetic Resonance (NMR) spectroscopy and Infrared (IR) spectroscopy were used to characterize these compounds. Furthermore, AutoDocking software was used to predict binding affinities of these thiazole-derived amides in silico. In silico, compound 6 exhibited the highest predicted binding affinity to PfPKG, while compound 5 had the lowest affinity. Compounds 1-4 displayed varying degrees of predicted binding affinity. In-vitro, it was found that compound 4 had the best percent inhibition, while compound 5 had the worst percent inhibition. Overall, all six compounds had weak inhibition (approximately 30-39% at 10 μM), but these results provide a foundation for future drug discovery experiments.

Keywords: Medicinal Chemistry, Malaria, drug discovery, PfPKG, Thiazole, Plasmodium

Procedia PDF Downloads 71
1041 Mechanical Characterization of Porcine Skin with the Finite Element Method Based Inverse Optimization Approach

Authors: Djamel Remache, Serge Dos Santos, Michael Cliez, Michel Gratton, Patrick Chabrand, Jean-Marie Rossi, Jean-Louis Milan

Abstract:

Skin tissue is an inhomogeneous and anisotropic material. Uniaxial tensile testing is one of the primary testing techniques for the mechanical characterization of skin at large scales. In order to predict the mechanical behavior of materials, the direct or inverse analytical approaches are often used. However, in case of an inhomogeneous and anisotropic material as skin tissue, analytical approaches are not able to provide solutions. The numerical simulation is thus necessary. In this work, the uniaxial tensile test and the FEM (finite element method) based inverse method were used to identify the anisotropic mechanical properties of porcine skin tissue. The uniaxial tensile experiments were performed using Instron 8800 tensile machine®. The uniaxial tensile test was simulated with FEM, and then the inverse optimization approach (or the inverse calibration) was used for the identification of mechanical properties of the samples. Experimentally results were compared to finite element solutions. The results showed that the finite element model predictions of the mechanical behavior of the tested skin samples were well correlated with experimental results.

Keywords: mechanical skin tissue behavior, uniaxial tensile test, finite element analysis, inverse optimization approach

Procedia PDF Downloads 392
1040 Mechanical-Reliability Coupling for a Bearing Capacity Assessment of Shallow Foundations

Authors: Amal Hentati, Mbarka Selmi, Tarek Kormi, Julien Baroth, Barthelemy Harthong

Abstract:

The impact of uncertainties on the performance assessment of shallow foundations is often significant. The need of the geotechnical engineers to a more objective and rigorous description of soil variations permitting to quantify these uncertainties and to incorporate them into calculation methods led to the development of reliability approaches. In this context, a mechanical-reliability coupling was developed in this paper, using a program coded in Matlab and the finite element software Abaqus, for the bearing capacity assessment of shallow foundations. The reliability analysis, based on the finite element method, assumed both soil cohesion and friction angle as uncertain parameters characterized by normal or lognormal probability distributions. The inherent spatial variability of both soil properties was, then, taken into account using 1D stationary random fields. The application of the proposed methodology to a shallow foundation subjected to a centered vertical loading permitted to highlight the proposed process interest. Findings proved the insufficiency of the conventional approach to predict the foundation failure and a high sensitivity of the ultimate loads to the soil properties uncertainties, mainly those related to the friction angle, was noted. Moreover, an asymmetry of both displacement and velocity fields was obtained.

Keywords: mechanical-reliability coupling, finite element method, shallow foundation, random fields, spatial variability

Procedia PDF Downloads 646
1039 Football Smart Coach: Analyzing Corner Kicks Using Computer Vision

Authors: Arth Bohra, Marwa Mahmoud

Abstract:

In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

Procedia PDF Downloads 159
1038 Prediction Factor of Recurrence Supraventricular Tachycardia After Adenosine Treatment in the Emergency Department

Authors: Chaiyaporn Yuksen

Abstract:

Backgroud: Supraventricular tachycardia (SVT) is an abnormally fast atrial tachycardia characterized by narrow (≤ 120 ms) and constant QRS. Adenosine was the drug of choice; the first dose was 6 mg. It can be repeated with the second and third doses of 12 mg, with greater than 90% success. The study found that patients observed at 4 hours after normal sinus rhythm was no recurrence within 24 hours. The objective of this study was to investigate the factors that influence the recurrence of SVT after adenosine in the emergency department (ED). Method: The study was conducted retrospectively exploratory model, prognostic study at the Emergency Department (ED) in Faculty of Medicine, Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand. The study was conducted for ten years period between 2010 and 2020. The inclusion criteria were age > 15 years, visiting the ED with SVT, and treating with adenosine. Those patients were recorded with the recurrence SVT in ED. The multivariable logistic regression model developed the predictive model and prediction score for recurrence PSVT. Result: 264 patients met the study criteria. Of those, 24 patients (10%) had recurrence PSVT. Five independent factors were predictive of recurrence PSVT. There was age>65 years, heart rate (after adenosine) > 100 per min, structural heart disease, and dose of adenosine. The clinical risk score to predict recurrence PSVT is developed accuracy 74.41%. The score of >6 had the likelihood ratio of recurrence PSVT by 5.71 times Conclusion: The clinical predictive score of > 6 was associated with recurrence PSVT in ED.

Keywords: clinical prediction score, SVT, recurrence, emergency department

Procedia PDF Downloads 138
1037 The Impact of Artificial Intelligence in the Development of Textile and Fashion Industry

Authors: Basem Kamal Abasakhiroun Farag

Abstract:

Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

Procedia PDF Downloads 38
1036 Prediction of Road Accidents in Qatar by 2022

Authors: M. Abou-Amouna, A. Radwan, L. Al-kuwari, A. Hammuda, K. Al-Khalifa

Abstract:

There is growing concern over increasing incidences of road accidents and consequent loss of human life in Qatar. In light to the future planned event in Qatar, World Cup 2022; Qatar should put into consideration the future deaths caused by road accidents, and past trends should be considered to give a reasonable picture of what may happen in the future. Qatar roads should be arranged and paved in a way that accommodate high capacity of the population in that time, since then there will be a huge number of visitors from the world. Qatar should also consider the risk issues of road accidents raised in that period, and plan to maintain high level to safety strategies. According to the increase in the number of road accidents in Qatar from 1995 until 2012, an analysis of elements affecting and causing road accidents will be effectively studied. This paper aims to identify and criticize the factors that have high effect on causing road accidents in the state of Qatar, and predict the total number of road accidents in Qatar 2022. Alternative methods are discussed and the most applicable ones according to the previous researches are selected for further studies. The methods that satisfy the existing case in Qatar were the multiple linear regression model (MLR) and artificial neutral network (ANN). Those methods are analyzed and their findings are compared. We conclude that by using MLR the number of accidents in 2022 will become 355,226 accidents, and by using ANN 216,264 accidents. We conclude that MLR gave better results than ANN because the artificial neutral network doesn’t fit data with large range varieties.

Keywords: road safety, prediction, accident, model, Qatar

Procedia PDF Downloads 240
1035 Adsorptive Performance of Surface Modified Montmorillonite in Vanadium Removal from Real Mine Water

Authors: Opeyemi Atiba-Oyewo, Taile Y. Leswfi, Maurice S. Onyango, Christian Wolkersdorfer

Abstract:

This paper describes the preparation of surface modified montmorillonite using hexadecyltrimethylammonium bromide (HDTMA-Br) for the removal of vanadium from mine water. The adsorbent before and after adsorption was characterised by Fourier transform infra-red (FT-IR), X-ray diffraction (XRD) and scanning electron microscopy (SEM), while the amount of vanadium adsorbed was determined by ICP-OES. The batch adsorption method was employed using vanadium concentrations in solution ranging from 50 to 320 mg/L and vanadium tailings seepage water from a South African mine. Also, solution pH, temperature and sorbent mass were varied. Results show that the adsorption capacity was affected by solution pH, temperature, sorbent mass and the initial concentration. Electrical conductivity of the mine water before and after adsorption was measured to estimate the total dissolved solids in the mine water. Equilibrium isotherm results revealed that vanadium sorption follows the Freundlich isotherm, indicating that the surface of the sorbent was heterogeneous. The pseudo-second order kinetic model gave the best fit to the kinetic experimental data compared to the first order and Elovich models. The results of this study may be used to predict the uptake efficiency of South Africa montmorillonite in view of its application for the removal of vanadium from mine water. However, the choice of this adsorbent for the uptake of vanadium or other contaminants will depend on the composition of the effluent to be treated.

Keywords: adsorption, vanadium, modified montmorillonite, equilibrium, kinetics, mine water

Procedia PDF Downloads 411
1034 Modified Model for UV-Laser Corneal Ablation

Authors: Salah Hassab Elnaby, Omnia Hamdy, Aziza Ahmed Hassan, Salwa Abdelkawi, Ibrahim Abdelhalim

Abstract:

Laser corneal reshaping has been proposed as a successful treatment of many refraction disorders. However, some physical and chemical demonstrations of the laser effect upon interaction with the corneal tissue are still not fully explained. Therefore, different computational and mathematical models have been implemented to predict the depth of the ablated channel and calculate the ablation threshold and the local temperature rise. In the current paper, we present a modified model that aims to answer some of the open questions about the ablation threshold, the ablation rate, and the physical and chemical mechanisms of that action. The proposed model consists of three parts. The first part deals with possible photochemical reactions between the incident photons and various components of the cornea (collagen, water, etc.). Such photochemical reactions may end by photo-ablation or just the electronic excitation of molecules. Then a chemical reaction is responsible for the ablation threshold. Finally, another chemical reaction produces fragments that can be cleared out. The model takes into account all processes at the same time with different probabilities. Moreover, the effect of applying different laser wavelengths that have been studied before, namely the common excimer laser (193-nm) and the solid state lasers (213-nm & 266-nm), has been investigated. Despite the success and ubiquity of the ArF laser, the presented results reveal that a carefully designed 213-nm laser gives the same results with lower operational drawbacks. Moreover, the use of mode locked laser could also decrease the risk of heat generation and diffusion.

Keywords: UV lasers, mathematical model, corneal ablation, photochemical ablation

Procedia PDF Downloads 64
1033 Developing a Hybrid Method to Diagnose and Predict Sports Related Concussions with Machine Learning

Authors: Melody Yin

Abstract:

Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.

Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time

Procedia PDF Downloads 152
1032 Effect of Constant and Variable Temperature on the Morphology of TiO₂ Nanotubes Prepared by Two-Step Anodization Method

Authors: Tayyaba Ghani, Mazhar Mehmood, Mohammad Mujahid

Abstract:

TiO₂ nanotubes are receiving immense attraction in the field of dye-sensitized solar cells due to their well-defined nanostructures, efficient electron transport and large surface area as compared to other one dimensional structures. In the present work, we have investigated the influence of temperature on the morphology of anodically produced self-organized Titanium oxide nanotubes (TiNTs). TiNTs are synthesized by two-step anodization method in an ethylene glycol based electrolytes containing ammonium fluoride. Experiments are performed at constant anodization voltage for two hours. An investigation by the SEM images reveals that if the temperature is kept constant during the anodizing experiment, variation in the average tube diameter is significantly reduced. However, if the temperature is not controlled then due to the exothermic nature of reactions for the formation of TiNTs, the temperature of electrolyte keep on increasing. This variation in electrolyte bath temperature introduced strong variations in tube diameter (20 nm to 160 nm) along the length of tubes. Current profiles, recorded during the anodization experiment, predict the effect of constant and varying experimental temperatures as well. In both cases, XRD results show the complete anatase crystal structure of nanotube upon annealing at 450 °C. Present work highlights the importance of constant temperature during the anodization experiments in order to develop an ordered array of nanotubes with a uniform tube diameter.

Keywords: anodization, ordering, temperature, TiO₂ nanotubes

Procedia PDF Downloads 154
1031 Destination Port Detection For Vessels: An Analytic Tool For Optimizing Port Authorities Resources

Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

Procedia PDF Downloads 101
1030 The Effect of Chemical Degradation of a Nonwoven Filter Media Membrane in Polyester

Authors: Rachid El Aidani, Phuong Nguyen-Tri, Toan Vu-Khanh

Abstract:

The filter media in synthetic fibre is the most geotextile materials used in aerosol and drainage filtration, particularly for buildings soil reinforcement in civil engineering due to its appropriated properties and its low cost. However, the current understanding of the durability and stability of this material in real service conditions, especially under severe long-term conditions are completely limited. This study has examined the effects of the chemical aging of a filter media in polyester non-woven under different temperatures (50, 70 and 80˚C) and pH (2. 7 and 12). The effect of aging conditions on mechanical properties, morphology, permeability, thermal stability and molar weigh changes is investigated. The results showed a significant reduction of mechanical properties in term of tensile strength, puncture force and tearing forces of the filter media after chemical aging due to the chemical degradation. The molar mass and mechanical properties changes in different temperature and pH showed a complex dependence of material properties on environmental conditions. The SEM and AFM characterizations showed a significant impact of the thermal aging on the morphological properties of the fibers. Based on the obtained results, the lifetime of the material in different temperatures was determined by the use of the Arrhenius model. These results provide useful information to better understand phenomena occurring during chemical aging of the filter media and may help to predict the service lifetime of this material in real used conditions.

Keywords: nonwoven membrane, chemical aging, mechanical properties, lifetime, filter media

Procedia PDF Downloads 303
1029 An Experimental Study on Service Life Prediction of Self: Compacting Concrete Using Sorptivity as a Durability Index

Authors: S. Girish, N. Ajay

Abstract:

Permeation properties have been widely used to quantify durability characteristics of concrete for assessing long term performance and sustainability. The processes of deterioration in concrete are mediated largely by water. There is a strong interest in finding a better way of assessing the material properties of concrete in terms of durability. Water sorptivity is a useful single material property which can be one of the measures of durability useful in service life planning and prediction, especially in severe environmental conditions. This paper presents the results of the comparative study of sorptivity of Self-Compacting Concrete (SCC) with conventionally vibrated concrete. SCC is a new, special type of concrete mixture, characterized by high resistance to segregation that can flow through intricate geometrical configuration in the presence of reinforcement, under its own mass, without vibration and compaction. SCC mixes were developed for the paste contents of 0.38, 0.41 and 0.43 with fly ash as the filler for different cement contents ranging from 300 to 450 kg/m3. The study shows better performance by SCC in terms of capillary absorption. The sorptivity value decreased as the volume of paste increased. The use of higher paste content in SCC can make the concrete robust with better densification of the micro-structure, improving the durability and making the concrete more sustainable with improved long term performance. The sorptivity based on secondary absorption can be effectively used as a durability index to predict the time duration required for the ingress of water to penetrate the concrete, which has practical significance.

Keywords: self-compacting concrete, service life prediction, sorptivity, volume of paste

Procedia PDF Downloads 306
1028 A Multi-Scale Approach for the Analysis of Fiber-Reinforced Composites

Authors: Azeez Shaik, Amit Salvi, B. P. Gautham

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Fiber reinforced polymer resin composite materials are finding wide variety of applications in automotive and aerospace industry because of their high specific stiffness and specific strengths when compared to metals. New class of 2D and 3D textile and woven fabric composites offer excellent fracture toughens as they bridge the cracks formed during fracture. Due to complexity of their fiber architectures and its resulting composite microstructures, optimized design and analysis of these structures is very complicated. A traditional homogenization approach is typically used to analyze structures made up of these materials. This approach usually fails to predict damage initiation as well as damage propagation and ultimate failure of structure made up of woven and textile composites. This study demonstrates a methodology to analyze woven and textile composites by using the multi-level multi-scale modelling approach. In this approach, a geometric repetitive unit cell (RUC) is developed with all its constituents to develop a representative volume element (RVE) with all its constituents and their interaction modeled correctly. The structure is modeled based on the RUC/RVE and analyzed at different length scales with desired levels of fidelity incorporating the damage and failure. The results are passed across (up and down) the scales qualitatively as well as quantitatively from the perspective of material, configuration and architecture.

Keywords: cohesive zone, multi-scale modeling, rate dependency, RUC, woven textiles

Procedia PDF Downloads 349
1027 Hydrological Characterization of a Watershed for Streamflow Prediction

Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: hydrological characteristic, stream flow, runoff discharge, land and climate

Procedia PDF Downloads 319
1026 Contextual and Personal Factors as Predictor of Academic Resilience among Female Undergraduates in Boko Haram Neighbourhood in North-Eastern Nigeria

Authors: Ndidi Ofole

Abstract:

Ongoing Boko Haram crisis and instability in North-Eastern Nigeria has placed additional stress on academic resilience of female undergraduates who are already challenged by gender discrimination in educational opportunities. Students without resilience lack stress hardiness to cope with academic challenges. There is a limited study on academic resilience targeting this disadvantaged population in Nigeria. Consequently, survey research design was employed to investigate the contextual and personal factors that could predict academic resilience among female undergraduates in Boko Haram Neighbourhood in North-Eastern, Nigeria. Five hundred and thirty female students with age range of 18 to 24 years ( = 19.2; SD=6.9) were randomly drawn from 3 Universities in North-Eastern Nigeria. They responded to five instruments, namely; Academic Resilience scale (r=0.72); Social Support questionnaire (r=0. 64); Social Connectedness questionnaire (r=0.75); Self-Efficacy scale (r=0. 68) and Emotional Regulation questionnaire (r=78). Results showed that there was significant positive relationship between the four independent variables and academic resilience. The variables jointly contributed 5.9% variance in the prediction of academic resilience. In terms of magnitude, social support was most potent while self-efficacy was the least. It concluded that the factors considered in this study are academic resilience facilitators. The outcomes of the study have both theoretical and practical implications.

Keywords: academic resilience, emotional regulation, school connectedness, self-efficacy , social support

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1025 A System Dynamics Approach to Technological Learning Impact for Cost Estimation of Solar Photovoltaics

Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

Abstract:

Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

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1024 Application of Acid Base Accounting to Predict Post-Mining Drainage Quality in Coalfields of the Main Karoo Basin and Selected Sub-Basins, South Africa

Authors: Lindani Ncube, Baojin Zhao, Ken Liu, Helen Johanna Van Niekerk

Abstract:

Acid Base Accounting (ABA) is a tool used to assess the total amount of acidity or alkalinity contained in a specific rock sample, and is based on the total S concentration and the carbonate content of a sample. A preliminary ABA test was conducted on 14 sandstone and 5 coal samples taken from coalfields representing the Main Karoo Basin (Highveld, Vryheid and Molteno/Indwe Coalfields) and the Sub-basins (Witbank and Waterberg Coalfields). The results indicate that sandstone and coal from the Main Karoo Basin have the potential of generating Acid Mine Drainage (AMD) as they contain sufficient pyrite to generate acid, with the final pH of samples relatively low upon complete oxidation of pyrite. Sandstone from collieries representing the Main Karoo Basin are characterised by elevated contents of reactive S%. All the studied samples were characterised by an Acid Potential (AP) that is less than the Neutralizing Potential (NP) except for two samples. The results further indicate that the sandstone from the Main Karoo Basin is prone to acid generation as compared to the sandstone from the Sub-basins. However, the coal has a relatively low potential of generating any acid. The application of ABA in this study contributes to an understanding of the complexities governing water-rock interactions. In general, the coalfields from the Main Karoo Basin have much higher potential to produce AMD during mining processes than the coalfields in the Sub-basins.

Keywords: Main Karoo Basin, sub-basin, coal, sandstone, acid base accounting (ABA)

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1023 The Relationship between Human Neutrophil Elastase Levels and Acute Respiratory Distress Syndrome in Patients with Thoracic Trauma

Authors: Wahyu Purnama Putra, Artono Isharanto

Abstract:

Thoracic trauma is trauma that hits the thoracic wall or intrathoracic organs, either due to blunt trauma or sharp trauma. Thoracic trauma often causes impaired ventilation-perfusion due to damage to the lung parenchyma. This results in impaired tissue oxygenation, which is one of the causes of acute respiratory distress syndrome (ARDS). These changes are caused by the release of pro-inflammatory mediators, plasmatic proteins, and proteases into the alveolar space associated with ongoing edema, as well as oxidative products that ultimately result in severe inhibition of the surfactant system. This study aims to predict the incidence of acute respiratory distress syndrome (ARDS) through human neutrophil elastase levels. This study examines the relationship between plasma elastase levels as a predictor of the incidence of ARDS in thoracic trauma patients in Malang. This study is an observational cohort study. Data analysis uses the Pearson correlation test and ROC curve (receiver operating characteristic curve). It can be concluded that there is a significant (p= 0.000, r= -0.988) relationship between elastase levels and BGA-3. If the value of elastase levels is limited to 23.79 ± 3.95, the patient will experience mild ARDS. While if the value of elastase levels is limited to 57.68 ± 18.55, in the future, the patient will experience moderate ARDS. Meanwhile, if the elastase level is between 107.85 ± 5.04, the patient will likely experience severe ARDS. Neutrophil elastase levels correlate with the degree of severity of ARDS incidence.

Keywords: ARDS, human neutrophil elastase, severity, thoracic trauma

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1022 NOx Prediction by Quasi-Dimensional Combustion Model of Hydrogen Enriched Compressed Natural Gas Engine

Authors: Anas Rao, Hao Duan, Fanhua Ma

Abstract:

The dependency on the fossil fuels can be minimized by using the hydrogen enriched compressed natural gas (HCNG) in the transportation vehicles. However, the NOx emissions of HCNG engines are significantly higher, and this turned to be its major drawback. Therefore, the study of NOx emission of HCNG engines is a very important area of research. In this context, the experiments have been performed at the different hydrogen percentage, ignition timing, air-fuel ratio, manifold-absolute pressure, load and engine speed. Afterwards, the simulation has been accomplished by the quasi-dimensional combustion model of HCNG engine. In order to investigate the NOx emission, the NO mechanism has been coupled to the quasi-dimensional combustion model of HCNG engine. The three NOx mechanism: the thermal NOx, prompt NOx and N2O mechanism have been used to predict NOx emission. For the validation purpose, NO curve has been transformed into NO packets based on the temperature difference of 100 K for the lean-burn and 60 K for stoichiometric condition. While, the width of the packet has been taken as the ratio of crank duration of the packet to the total burnt duration. The combustion chamber of the engine has been divided into three zones, with the zone equal to the product of summation of NO packets and space. In order to check the accuracy of the model, the percentage error of NOx emission has been evaluated, and it lies in the range of ±6% and ±10% for the lean-burn and stoichiometric conditions respectively. Finally, the percentage contribution of each NO formation has been evaluated.

Keywords: quasi-dimensional combustion , thermal NO, prompt NO, NO packet

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1021 Influence of AAR-Induced Expansion Level on Confinement Efficiency of CFRP Wrapping Applied to Damaged Circular Concrete Columns

Authors: Thamer Kubat, Riadh Al Mahiadi, Ahmad Shayan

Abstract:

The alkali-aggregate reaction (AAR) in concrete has a negative influence on the mechanical properties and durability of concrete. Confinement by carbon fiber reinforced polymer (CFRP) is an effective method of treatment for some AAR-affected elements. Eighteen reinforced columns affected by different levels of expansion due to AAR were confined using CFRP to evaluate the effect of expansion level on confinement efficiency. Strength and strain capacities (axial and circumferential) were measured using photogrammetry under uniaxial compressive loading to evaluate the efficiency of CFRP wrapping for the rehabilitation of affected columns. In relation to uniaxial compression capacity, the results indicated that the confinement of AAR-affected columns by one layer of CFRP is sufficient to reach and exceed the load capacity of unaffected sound columns. Parallel to the experimental study, finite element (FE) modeling using ATENA software was employed to predict the behavior of CFRP-confined damaged concrete and determine the possibility of using the model in a parametric study by simulating the number of CFRP layers. A comparison of the experimental results with the results of the theoretical models showed that FE modeling could be used for the prediction of the behavior of confined AAR-damaged concrete.

Keywords: ATENA, carbon fiber reinforced polymer (CFRP), confinement efficiency, finite element (FE)

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1020 The Effect of Training and Development Practice on Employees’ Performance

Authors: Sifen Abreham

Abstract:

Employees are resources in organizations; as such, they need to be trained and developed properly to achieve an organization's goals and expectations. The initial development of the human resource management concept is based on the effective utilization of people to treat them as resources, leading to the realization of business strategies and organizational objectives. The study aimed to assess the effect of training and development practices on employee performance. The researcher used an explanatory research design, which helps to explain, understand, and predict the relationship between variables. To collect the data from the respondents, the study used probability sampling. From the probability, the researcher used stratified random sampling, which can branch off the entire population into homogenous groups. The result was analyzed and presented by using the statistical package for the social science (SPSS) version 26. The major finding of the study was that the training has an impact on employees' job performance to achieve organizational objectives. The district has a policy and procedure for training and development, but it doesn’t apply actively, and it’s not suitable for district-advised reform this policy and procedure and applied actively; the district gives training for the majority of its employees, but most of the time, the training is theoretical the district advised to use practical training method to see positive change, the district gives evaluation after the employees take training and development, but the result is not encouraging the district advised to assess employees skill gap and feel that gap, the district has a budget, but it’s not adequate the district advised to strengthen its financial ground.

Keywords: training, development, employees, performance, policy

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