Search results for: irrigationaxial flux machines

Authors: Yuan-Ching Chiang, Chien-Yeh Hsu, Chen Chih-Hao, Sih-Li Chen

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The p-n junction temperature of LEDs directly influences their operating life and luminous efficiency. An excessively high p-n junction temperature minimizes the output flux of LEDs, decreasing their brightness and influencing the photon wavelength; consequently, the operating life of LEDs decreases and their luminous output changes. The maximum limit of the p-n junction temperature of LEDs is approximately 120 °C. The purpose of this research was to devise an approach for dissipating heat generated in a confined space when LEDs operate at low temperatures to reduce light decay. The cooling mode of existing commercial LED lights can be divided into natural- and forced convection cooling. In natural convection cooling, the volume of LED encapsulants must be increased by adding more fins to increase the cooling area. However, this causes difficulties in achieving efficient LED lighting at high power. Compared with forced convection cooling, heat transfer through water convection is associated with a higher heat transfer coefficient per unit area; therefore, we dissipated heat by using a closed loop water cooling system. Nevertheless, cooling water exposed to air can be easily influenced by environmental factors. Thus, we incorporated a ground heat exchanger into the water cooling system to minimize the influence of air on cooling water and then observed the relationship between the amounts of heat dissipated through the ground and LED efficiency.

Keywords: helical ground heat exchanger, high power LED, ground source cooling system, heat dissipation

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Authors: Vu H. N. Khue, Marian Pavelka, Georg Jocher, Jiří Dušek, Le T. Son, Bui T. An, Ho Q. Bang, Pham Q. Huong

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Agriculture is an important economic sector of Vietnam, the most popular of which is wet rice cultivation. These activities are also known as the main contributor to the national greenhouse gas. In order to understand more about greenhouse gas exchange in these activities and to investigate the factors influencing carbon cycling and sequestration in these types of ecosystems, since 2019, the first eddy covariance station has been installed in a paddy field in Long An province, Mekong Delta. The station was equipped with state-of-the-art equipment for CO₂ and CH₄ gas exchange and micrometeorology measurements. In this study, data from the station was processed following the ICOS recommendations (Integrated Carbon Observation System) standards for CO₂, while CH₄ was manually processed and gap-filled using a random forest model from methane-gapfill-ml, a machine learning package, as there is no standard method for CH₄ flux gap-filling yet. Finally, the carbon equivalent (Ce) balance based on CO₂ and CH₄ fluxes was estimated. The results show that in 2020, even though a new water management practice - alternate wetting and drying - was applied to reduce methane emissions, the paddy field released 928 g Cₑ.m⁻².yr⁻¹, and in 2021, it was reduced to 707 g Cₑ.m⁻².yr⁻¹. On a provincial level, rice cultivation activities in Long An, with a total area of 498,293 ha, released 4.6 million tons of Cₑ in 2020 and 3.5 million tons of Cₑ in 2021.

Keywords: eddy covariance, greenhouse gas, methane, rice cultivation, Mekong Delta

Procedia PDF Downloads 133

Authors: Manpreet Kaur

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The effect of external and internal exposure in outdoor and indoor environment can be significantly gauged by natural radionuclides. Therefore, it is a consequential to approximate the level of radionuclide contents in soil samples of any area and the risks associated with it. Rate of radon emerging from soil is also one of the prominent parameters for the assessment of radon levels in environmental. In present study, natural radionuclide contents viz. ²³²Th, ²³⁸U and ⁴⁰K and radon/thoron exhalation rates were evaluated operating thallium doped sodium iodide gamma radiation detector and advanced Smart Rn Duo technique in the soil samples from 30 villages of Jammu district, Jammu and Kashmir, India. Radon flux rate was also measured by using surface chamber technique. Results obtained with two different methods were compared to investigate the cause of emanation factor in the soil profile. The radon mass exhalation rate in the soil samples has been found varying from 15 ± 0.4 to 38 ± 0.8 mBq kg⁻¹ h⁻¹ while thoron surface exhalation rate has been found varying from 90 ± 22 to 4880 ± 280 Bq m⁻² h⁻¹. The mean value of radium equivalent activity (99 ± 27 Bq kg⁻¹) was appeared to be well within the admissible limit of 370 Bq kg⁻¹ suggested by Organization for Economic Cooperation and Development (2009) report. The values of various parameters related to radiological hazards were also calculated and all parameters have been found to be well below the safe limits given by various organizations. The outcomes pointed out that region was protected from danger as per health risks effects associated with these radionuclide contents is concerned.

Keywords: absorbed dose rate, exhalation rate, human health, radionuclide

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Authors: Kaouther Bergaui, Nafaa Reguigui, Charles Gary

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Characterization and the applications of deuterium-deuterium (DD) neutron generator developed by Adelphie technology and acquired by the National Centre of Nuclear Science and Technology (NCNST) were presented in this work. We study the performance of the neutron generator in terms of neutron yield, production efficiency, and the ionic current as a function of the acceleration voltage at various RF powers. We provide the design and optimization of the PGNAA chamber and thus give insight into the capabilities of the planned PGNAA facility. Additional non-destructive techniques were studied employing the DD neutron generator, such as PGNAA and neutron radiography: The PGNAA is used for determining the concentration of 10B in Si and SiO2 matrices by using a germanium detector HPGe and the results obtained are compared with PGNAA system using a Sodium Iodide detector (NaI (Tl)); Neutron radiography facility was tested and simulated, using a camera device CCD and simulated by the Monte Carlo code; and the explosive detection system (EDS) also simulated using the Monte Carlo code. The study allows us to show that the new models of DD neutron generators are feasible and that superior-quality neutron beams could be produced and used for various applications. The feasibility of Boron neutron capture therapy (BNCT) for cancer treatment using a neutron generator was assessed by optimizing Beam Shaping Assembly (BSA) on a phantom using Monte-Carlo (MCNP6) simulations.

Keywords: neutron generator deuterium-deuterium, Monte Carlo method, radiation, neutron flux, neutron activation analysis, born, neutron radiography, explosive detection, BNCT

Procedia PDF Downloads 186

Authors: Chokri Slim

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The objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims.

Keywords: credit risk management, multiple linear regression, principal components analysis, artificial neural networks, support vector machines

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Authors: Safoin Aktaou, Aya Al Masri, Kamel Guerchouche, Malorie Martin, Fouad Maaloul

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Introduction: In the ‘Magnetic Resonance Imaging (MRI)’ department, all workers involved in preparing the patient, setting it up, tunnel cleaning, etc. are likely to be exposed to ‘ElectroMagnetic fields (EMF)’ emitted by the MRI device. Exposure to EMF can cause adverse radio-biological effects to workers. The purpose of this study is to propose an organizational process to manage and control EMF risks. Materials and methods: The study was conducted at seven MRI departments using machines with 1.5 and 3 Tesla magnetic fields. We assessed the exposure of each one by measuring the two electromagnetic fields (static and dynamic) at different distances from the MRI machine both inside and around the examination room. Measurement values were compared with British and American references (those of the UK's ‘Medicines and Healthcare Regulatory Agency (MHRA)’ and the ‘American Radiology Society (ACR)’). Results: Following the results of EMF measurements and their comparison with the recommendations of learned societies, a zoning system that adapts to needs of different MRI services across the country has been proposed. In effect, three risk areas have been identified within the MRI services. This has led to the development of a good practice guide related to the magnetic protection of MRI workers. Conclusion: The guide established by our study is a standard that allows MRI workers to protect themselves against the risk of electromagnetic fields.

Keywords: comparison with international references, measurement of electromagnetic fields, magnetic protection of workers, magnetic resonance imaging

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Authors: A. Alao Olumuyiwa

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Health hazards reported to be associated with exposure to electromagnetic radiations which include brain tumors, genotoxic effects, neurological effects, immune system deregulation, allergic responses and some cardiovascular effects are discussed under a closed tabular model in this study. This review however showed that there is strong and robust evidence that chronic exposures to electromagnetic frequency across the spectrum, through strength, consistency, biological plausibility and many dose-response relationships, may result in brain cancer and other carcinogenic disease symptoms. There is therefore no safe threshold because of the genotoxic nature of the mechanism that may however be involved. The discussed study explains that the cell phone has induced effects upon the blood –brain barrier permeability and the cerebellum exposure to continuous long hours RF radiation may result in significant increase in albumin extravasations. A physical Biomodeling approach is however employed to review this health effects using Specific Absorption Rate (SAR) of different GSM machines to critically examine the symptoms such as a decreased loco motor activity, increased grooming and reduced memory functions in a variety of animal spices in classified grouped and sub grouped models.

Keywords: brain cancer, electromagnetic radiations, physical biomodeling, specific absorption rate (SAR)

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Authors: Nur Sarma, Paul M. Tuohy, Siniša Djurović

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This paper presents an in-depth investigation of the effects of several grid supply harmonic voltages on the stator currents of an example wound rotor induction machine. The observed effects of higher order grid supply harmonics are identified using a finite element time stepping transient model, as well as a time-stepping electromagnetic model. In addition, a number of analytical equations to calculate the spectral content of the stator currents are presented in the paper. The presented equations are validated through comparison with the obtained spectra predicted using the finite element and electromagnetic models. The presented study provides a better understanding of the origin of supply harmonic effects identified in the stator currents of the example wound rotor induction machine. Furthermore, the study helps to understand the effects of higher order supply harmonics on the harmonic emissions of the wound rotor induction machine.  

Keywords: wound rotor induction machine, supply harmonics, current spectrum, power spectrum, power quality, harmonic emmisions, finite element analysis

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Authors: Mohamed Eltarabily, Abdelazim Negm, Chihiro Yoshimura

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Recently, the pollution of groundwater from the use of nitrogenous fertilizer is at the increase. Also, due to the increase in area under cultivation and regular use of fertilizer in irrigated agriculture, groundwater pollution from agricultural activities is becoming a major concern. Because of the high mobility of Nitrate (NO3-) in soil which is governed by electrostatic processes, particularly anion exclusion, nitrate can be intercepted by shallow subsurface drainage pipe systems and then discharged offsite into streams, rivers, and lakes causing many hazards. In order to solve these environmental problems associated with nitrate, a better understanding of how NO3- moves through the soil profile under flow conditions is required. In the present paper, the results of a comparative study between experimental and numerical modeling of Nitrate transport through a saturated soil column are presented and analyzed. In order to achieve that, three water fluxes densities; 0.008, 0.007, and 0.006 m sec-1 and N concentration rates 10 mol cm-3 were used. The same concentrations were used in the simulation using HYDRUS-2D. The physical and chemical properties of the collected soil samples were calculated. Besides, the soil texture was determined which was silty sand. Results showed that HYDRUS-2D can successfully predict the relative behavior of N transport in the present experiment. Nitrate concentrations will reach deeper depth with the increase in the water flux. Overall, it was overestimated in the final concentration of (NO3-) in the soil by numerical simulation than by experimental column test. The column experiment is a useful tool for assessing the nitrate concentrations in the soil profile.

Keywords: groundwater, nitrate leaching, HYDRUS-2D, soil column

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Authors: Yasser Mahmoudi, Nader Karimi

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The present work examines analytically the effect internal heat generation on temperature fields in a channel partially-filled with a porous under local thermal non-equilibrium condition. The Darcy-Brinkman model is used to represent the fluid transport through the porous material. Two fundamental models (models A and B) represent the thermal boundary conditions at the interface between the porous medium and the clear region. The governing equations of the problem are manipulated, and for each interface model, exact solutions for the solid and fluid temperature fields are developed. These solutions incorporate the porous material thickness, Biot number, fluid to solid thermal conductivity ratio Darcy number, as the non-dimensional energy terms in fluid and solid as parameters. Results show that considering any of the two models and under zero or negative heat generation (heat sink) and for any Darcy number, an increase in the porous thickness increases the amount of heat flux transferred to the porous region. The obtained results are applicable to the analysis of complex porous media incorporating internal heat generation, such as heat transfer enhancement (THE), tumor ablation in biological tissues and porous radiant burners (PRBs).

Keywords: porous media, local thermal non-equilibrium, forced convection, heat transfer, exact solution, internal heat generation

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Authors: García López

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The Government Departments of Health have the task of informing and educating citizens about public health issues. For this, they use channels like Twitter, key in the search for health information and the propagation of content. The tweets, important in the virality of the content, may contain emotions that influence the contagion and exchange of knowledge. The goal of this study is to perform an analysis of the emotional projection of health information shared on Twitter by official American accounts: the disease control account CDCgov, National Institutes of Health, NIH, the government agency HHSGov, and the professional organization PublicHealth. For this, we used Tone Analyzer, an International Business Machines Corporation (IBM) tool specialized in emotion detection in text, corresponding to the categorical model of emotion representation. For 15 days, all tweets from these accounts were analyzed with the emotional analysis tool in text. The results showed that their tweets contain an important emotional load, a determining factor in the success of their communications. This exposes that official accounts also use subjective language and contain emotions. The predominance of emotion joy over sadness and the strong presence of emotions in their tweets stimulate the virality of content, a key in the work of informing that government health departments have.

Keywords: emotions in tweets, emotion detection in the text, health information on Twitter, American health official accounts, emotions on Twitter, emotions and content

Procedia PDF Downloads 132

Authors: Mehmet Savsar, Majid Aldaihani

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Flexible Manufacturing Systems (FMS) are used to produce a variety of parts on the same equipment. Therefore, their utilization is higher than traditional machining systems. Higher utilization, on the other hand, results in more frequent equipment failures and additional need for maintenance. Therefore, it is necessary to carefully analyze operational characteristics and productivity of FMS or Flexible Manufacturing Cells (FMC), which are smaller configuration of FMS, before installation or during their operation. Appropriate models should be developed to determine production rates based on operational conditions, including equipment reliability, availability, and repair capacity. In this paper, a stochastic model is developed for an automated FMC system, which consists of two machines served by two robots and a single repairman. The model is used to determine system productivity and equipment utilization under different operational conditions, including random machine failures, random repairs, and limited repair capacity. The results are compared to previous study results for FMC system with sufficient repair capacity assigned to each machine. The results show that the model will be useful for design engineers and operational managers to analyze performance of manufacturing systems at the design or operational stages.

Keywords: flexible manufacturing, FMS, FMC, stochastic modeling, production rate, reliability, availability

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Authors: Oranso T. Mahlangi, Bhekie B. Mamba

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The occurrence of trace organic compounds (TOrCs) in water has raised health concerns for living organisms. The majority of TorCs, including pharmaceuticals and volatile organic compounds, are poorly monitored, partly due to the high cost of analysis and less strict water quality guidelines in South Africa. Therefore, the removal of TorCs is important to guarantee safe potable water. In this study, ZnO nanoparticles were fabricated in situ in polyethersulfone (PES) polymer solutions. This was followed by membrane synthesis using the phase inversion technique. Techniques such as FTIR, Raman, SEM, AFM, EDS, and contact angle measurements were used to characterize the membranes for several physicochemical properties. The membranes were then evaluated for their efficiency in treating pharmaceutical wastewater and resistance to organic (sodium alginate) and protein (bovine serum albumin) fouling. EDS micrographs revealed uniform distribution of ZnO nanoparticles within the polymer matrix, while SEM images showed uniform fingerlike structures. The addition of ZnO increased membrane roughness as well as hydrophilicity (which in turn improved water fluxes). The membranes poorly rejected monovalent and divalent salts (< 10%), making them resistant to flux decline due to concentration polarization effects. However, the membranes effectively removed carbamazepine, caffeine, sulfamethoxazole, ibuprofen, and naproxen by over 50%. ZnO PES membranes were resistant to organic and protein fouling compared to the neat membrane. ZnO PES ultrafiltration membranes may provide a solution in the reclamation of wastewater.

Keywords: trace organic compounds, pharmaceuticals, membrane fouling, wastewater reclamation

Procedia PDF Downloads 134

Authors: Sheimah El Bejjaji, Lara Gorsek, Chandler Quilchez, Joaquim Suñer, Mireia Mallandrich

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Flurbiprofen is an anti-inflammatory drug used in several treatments. The purpose of this study was to compare the permeation of two different formulations of flurbiprofen through the human skin. The first formulation was a solution of flurbiprofen dissolved with polyethylene glycol 3350 (PEG 3350). The second formulation was flurbiprofen encapsulated in poly-ɛ-caprolactone (PɛCL) nanoparticles (NPs), stabilized with poloxamer 188, submitted individually for freeze-drying with PEG 3350 as a cryoprotectant and sterilized by gamma-irradiation. Human skin was obtained from the abdominal region of a healthy patient. The experimental protocol was approved by the Bioethics Committee of Barcelona SCIAS Hospital (Spain), and they obtained the written informed consent forms. After being frozen to -20ºC, the skin samples were cut with a dermatome at 400 µm. The ex vivo permeation study was performed in Franz diffusion cells with a diffusion area of 2.54 cm². Skin samples were placed between two compartment sites, the dermal side in contact with the receptor medium and the epidermis side in contact with the donor chamber to which the formulation was applied. The permeation study was conducted for 24 hours at 32 ± 0.5 °C in accordance with sink conditions. The results were analyzed with an unpaired t-test, and the p-values indicate the formulation with nanoparticles had a higher permeability coefficient, flux, partition parameter, diffusion parameter, and lag time. The applicability of this formulation topically can benefit articulations and ligament inflammation as an alternative to oral drugs.

Keywords: anti-inflammatory drug, flurbiprofen, human skin, nanoparticles, skin permeation

Procedia PDF Downloads 84

Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: Vasudha Chaturvedi, Mauro Guglielmin, Nicoletta Canone, Chiara Casiraghi, Francesco Griforni, Lorenzo Tonin, Silvia Piconne, Ilaria Bonfati, Filippo Caccia, Stefano Ponti

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The study explores the complex interplay between abiotic factors and methane emissions in Arctic environments. It highlights the challenges in understanding these relationships across different vegetation communities and seasons, considering the influence of multiple drivers. In the spring and early winter of 2023, we investigated net methane fluxes and 55 environmental parameters at three distinct sites in Alaska representing wet tundra, tussock, and dry heath using closed chamber techniques. Each site underwent three measurement cycles over consecutive days. Our findings reveal that tussock exhibited the highest methane emissions (ranging from 17 to 44 nmol m-2 s-1), followed by wet tundra (3 to 38 nmol m-2 s-1), while the dry heath consistently consumed methane across all seasons (-1.2 nmol m-2 s-1). Diurnal flux patterns at tussock sites peaked in the afternoon towards beginning of winter season, with correlations observed between fluxes and water content at 20 cm depth across all sites, and additionally with ground surface temperature (GST) temperature and water content at 0–60 cm depth at one site. Wet sites displayed higher correlations with GST up to 60 cm depth. These findings underscore the importance of considering site-specific dynamics and multiple environmental variables in understanding methane emissions from Arctic ecosystems.

Keywords: climate change, cryosphere, methane fluxes, soil, ground temperature

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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Authors: Ruquan You, Haiwang Li, Zhi Tao

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A time-resolved particle image velocimetry (PIV) system is developed to investigate the boundary layer flow with the effect of rotating Coriolis and buoyancy force. This time-resolved PIV system consists of a 10 Watts continuous laser diode and a high-speed camera. The laser diode is able to provide a less than 1mm thickness sheet light, and the high-speed camera can capture the 6400 frames per second with 1024×1024 pixels. The whole laser and the camera are fixed on the rotating facility with 1 radius meters and up to 500 revolutions per minute, which can measure the boundary flow velocity in the rotating channel with and without ribs directly at rotating conditions. To investigate the effect of buoyancy force, transparent heater glasses are used to provide the constant thermal heat flux, and then the density differences are generated near the channel wall, and the buoyancy force can be simulated when the channel is rotating. Due to the high temporal and spatial resolution of the system, the proper orthogonal decomposition (POD) can be developed to analyze the characteristic of the turbulent boundary layer flow at rotating conditions. With this rotating facility and PIV system, the velocity profile, Reynolds shear stress, spatial and temporal correlation, and the POD modes of the turbulent boundary layer flow can be discussed.

Keywords: rotating facility, PIV, boundary layer flow, spatial and temporal resolution

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Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

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Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control

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Authors: Kanit Aroonrat, Somchai Wongwises

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A heat exchanger is one of the vital parts in a wide variety of applications. The tube with surface modification is generally referred to as an enhanced tube. With this, the thermal performance of the heat exchanger is improved. A dimpled tube is one of many kinds of enhanced tube. The heat transfer and pressure drop of two-phase flow inside dimpled tubes have received little attention in the literature, despite of having an important role in the development of refrigeration and air conditioning systems. As a result, the main aim of this study is to investigate the condensation heat transfer and pressure drop of refrigerant-134a flowing inside dimpled tubes. The test section is a counter-flow double-tube heat exchanger, which the refrigerant flows in the inner tube and water flows in the annulus. The inner tubes are one smooth tube and three dimpled tubes with different helical pitches. All test tubes are made from copper with an inside diameter of 8.1 mm and length of 1500 mm. The experiments are conducted over mass fluxes ranging from 300 to 500 kg/m²s, heat flux ranging from 10 to 20 kW/m², and condensing temperature ranging from 40 to 50 ˚C. The results show that all dimpled tubes provide higher heat transfer coefficient and frictional pressure drop compared to the smooth tube. In addition, the heat transfer coefficient and frictional pressure drop increase with decreasing of helical pitch. It can be observed that the dimpled tube with lowest helical pitch yields the heat transfer enhancement in the range of 60-89% with the frictional pressure drop increase of 289-674% in comparison to the smooth tube.

Keywords: condensation, dimpled tube, heat transfer, pressure drop

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Authors: J. P. Panda, K. Sasmal, H. V. Warrior

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Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD

Procedia PDF Downloads 194

Authors: Paula C. Latorre Arroyo, Andrea C. Latorre Arroyo

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In the present society, children are exposed to and impacted by technology from very early on in various ways. Artificial intelligence (AI), in particular, directly affects them, be it positively or negatively. The concept of artificial intelligence is commonly defined as the technological programming of computers or robotic mechanisms with humanlike capabilities and characteristics. These technologies are often designed as helpful machines or disguised as handy tools that could ultimately steal private information for illicit purposes. Children, being one of the most vulnerable groups due to their lack of experience and knowledge, do not have the ability to recognize or have the malice to distinguish if an apparatus with artificial intelligence is good or bad for them. For this reason, as a society, there must be a sense of responsibility to regulate and monitor different types of uses for artificial intelligence to protect children from potential risks that might arise. This article aims to investigate the many implications that artificial intelligence has in the lives of children, starting from a home setting, within the classroom, and, ultimately, in online spaces. Irrefutably, there are numerous beneficial aspects to the use of artificial intelligence. However, due to its limitless potential and lack of specific and substantial regulations to prevent the illicit use of this technology, safety and privacy concerns surface, specifically regarding the youth. This written work aims to provide an in-depth analysis of how artificial intelligence can both help children and jeopardize their safety. Concluding with resources and data supporting the aforementioned statement.

Keywords: artificial intelligence, children, privacy, rights, safety

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Authors: Wasiu Oyeleke Oyediran

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Maize is a common staple food for human consumption and livestock feeds. It provides employment and means of livelihood for women in both rural areas and urban centres in Nigeria. However, the entrepreneurial skills of women engaged in its processing and value addition has not been fully enhanced. This study was therefore carried out to investigate rural women entrepreneurial skills in maize processing and value addition in Ogun State, Nigeria. Snow ball sampling technique was used in the selection of 70 respondents for this study. Data were analyzed with descriptive statistics and chi-square. Results revealed that majority (50.0%) of the respondents were 31 - 40 years of age and 60% of the respondents had spent 6 – 10 years in maize processing. The respondents have great entrepreneurial skills in popcorn (85.7%), corn cake (80.0%), corn balls (64.3%) and kokoro (52.9%) making. The majority of the respondents accessed information and entrepreneurial skills through fellow processors (88.6%) and friends and neighbours (62.9%). Major constraints to maize processing and value addition were scarcity of raw materials during off season periods (95.7%), ineffective preservation methods (88.6%), lack of modern processing equipment (82.9%), and high cost of processing machines (72.9%). Result of chi-square showed that there is significant association between personal characteristics of the respondents and entrepreneurial skills of the women at p < 0.05. It is hereby recommended that subsidized processing equipment should be made available to the maize processors in the study area by the government and NGOs.

Keywords: women, entreprenuerial skills, maize prcessing, value addition

Procedia PDF Downloads 211

Authors: Yongmin You

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Electric machines for office automation device such as printer and scanner have been required the low noise and vibration performance. Many researches about the low noise and vibration of polygon mirror scanner motor have been also progressed. The noise and vibration of polygon mirror scanner motor can be classified by aerodynamic, structural and electromagnetic. Electromagnetic noise and vibration can be occurred by high cogging torque and nonsinusoidal back EMF. To improve the cogging torque and back EMF characteristic, we apply unequal air-gap. To analyze characteristic of a polygon mirror scanner motor, two dimensional finite element method is used. To minimize the cogging torque of a polygon mirror motor, Kriging based on latin hypercube sampling (LHS) is utilized. Compared to the initial model, the torque ripple of the optimized unequal air-gap model was reduced by 23.4 % while maintaining the back EMF and average torque. To verify the optimal design results, the experiment was performed. We measured the vibration in motors at 23,600 rpm which is the rated velocity. The radial and axial gravitational acceleration of the optimal model were declined more than seven times and three times, respectively. From these results, a shape optimized unequal polygon mirror scanner motor has shown the usefulness of an improvement in the torque ripple and electromagnetic vibration characteristic.

Keywords: polygon mirror scanner motor, optimal design, finite element method, vibration

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Authors: Carlos G. Santos, Frederico A. Genezini, A. P. Dos Santos, H. Yorivaz, P. T. D. Siqueira

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The Prompt-Gamma Activation Analysis (PGAA) is a valuable technique for investigating the elemental composition of various samples. However, the installation of a PGAA system entails specific conditions such as filtering the neutron beam according to the target and providing adequate shielding for both users and detectors. These requirements incur substantial costs, exceeding $100,000, including manpower. Nevertheless, a cost-effective approach involves leveraging an existing neutron beam facility to create a hybrid system integrating PGAA and Neutron Tomography (NT). The IEA-R1 nuclear reactor at IPEN/USP possesses an NT facility with suitable conditions for adapting and implementing a PGAA device. The NT facility offers a thermal flux slightly colder and provides shielding for user protection. The key additional requirement involves designing detector shielding to mitigate high gamma ray background and safeguard the HPGe detector from neutron-induced damage. This study employs Monte Carlo simulations with the MCNP6 code to optimize the collimator plug for PGAA within the IEA-R1 NT facility. Three collimator models are proposed and simulated to assess their effectiveness in shielding gamma and neutron radiation from nucleon fission. The aim is to achieve a focused prompt-gamma signal while shielding ambient gamma radiation. The simulation results indicate that one of the proposed designs is particularly suitable for the PGAA-NT hybrid system.

Keywords: MCNP6.1, neutron, prompt-gamma ray, prompt-gamma activation analysis

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Authors: Ahmad Shanei, Milad Baradaran-Ghahfarokhi

Abstract:

This study aimed to investigate testicular dose (TD) and the associated risk of heritable disease from common pelvis radiotherapy of male patients in Iran. In this work, the relation between TD and changes in beam energy, pelvis size, source to skin distance (SSD) and beam directions (anterior or posterior) were also evaluated. The values of TDs were measured on 67 randomly selected male patients during common pelvis radiotherapy using 1.17 and 1.33 MeV, Theratron Cobalt-60 unit at SSD of 80 cm and 9 MV, Neptun 10 PC and 18 MV, GE Saturne 20 at SSD of 100 cm at Seyed-Al Shohada Hospital, Isfahan, Iran. Results showed that the maximum TD was up to 12% of the tumor dose. Considering the risk factor for radiation-induced heritable disorders of 0.1% per Sv, an excess risk of hereditary disorders of 72 per 10000 births was conservatively calculated. There was a significant difference in the measured TD using different treatment machines and energies (P < 0.001). The TD at 100 cm SSD were much less than that for 80 cm SSD (P <0.001). The Pearson Correlation test showed that, as expected, there was a strong correlation between TD and patient’s pelvis size (r = 0.275, P <0.001). Using the student’s t-tests, it was found that, there was not a significant difference between TD and beam direction (P = 0.231). Iranian male patients undergoing pelvic radiotherapy have the potential of receiving a TD of more than 1 Gy which might result in temporary azoospermia. The risk for induction of hereditary disorders in future generations should be considered as low but not negligible in comparison with the correspondent nominal risk.

Keywords: pelvis radiotherapy, testicular dose, infertility, hereditary effects

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Authors: Victoria L. Chester, Usha Kuruganti

Abstract:

The forest industry is a major economic sector of Canada and also one of the most dangerous industries for workers. The use of mechanized mobile forestry harvesting machines has successfully reduced the incidence of injuries in forest workers related to manual labor. However, these machines have also created additional concerns, including a high machine operation learning curve, increased the length of the workday, repetitive strain injury, cognitive load, physical and mental fatigue, and increased postural loads due to sitting in a confined space. It is critical to obtain objective performance data for employers to develop appropriate work practices for this industry, however ergonomic field studies of this industry are lacking mainly due to the difficulties in obtaining comprehensive data while operators are cutting trees in the woods. The purpose of this study was to establish a measurement and experimental protocol to examine the effects of worker skill level and movement training speed (joystick crane speed) on harvesting performance using a forestry simulator. A custom wrist angle measurement device was developed as part of the study to monitor Euler angles during operation of the simulator. The device of the system consisted of two accelerometers, a Bluetooth module, three 3V coin cells, a microcontroller, a voltage regulator and an application software. Harvesting performance and crane data was provided by the simulator software and included tree to frame collisions, crane to tree collisions, boom tip distance, number of trees cut, etc. A pilot study of 3 operators with various skill levels was tested to identify factors that distinguish highly skilled operators from novice or intermediate operators. Dependent variables such as reaction time, math skill, past work experience, training movement speed (e.g. joystick control speeds), harvesting experience level, muscle activity, and wrist biomechanics were measured and analyzed. A 10-channel wireless surface EMG system was used to monitor the amplitude and mean frequency of 10 upper extremity muscles during pre and postperformance on the forestry harvest stimulator. The results of the pilot study showed inconsistent changes in median frequency pre-and postoperation, but there was the increase in the activity of the flexor carpi radialis, anterior deltoid and upper trapezius of both arms. The wrist sensor results indicated that wrist supination and pronation occurred more than flexion and extension with radial-ulnar rotation demonstrating the least movement. Overall, wrist angular motion increased as the crane speed increased from slow to fast. Further data collection is needed and will help industry partners determine those factors that separate skill levels of operators, identify optimal training speeds, and determine the length of training required to bring new operators to an efficient skill level effectively. In addition to effective and employment training programs, results of this work will be used for selective employee recruitment strategies to improve employee retention after training. Further, improved training procedures and knowledge of the physical and mental demands on workers will lead to highly trained and efficient personnel, reduced risk of injury, and optimal work protocols.

Keywords: EMG, forestry, human factors, wrist biomechanics

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

Abstract:

With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

Abstract:

Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

Procedia PDF Downloads 105

Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi

Abstract:

Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.

Keywords: biometric measurements, fetal head malformations, machine learning methods, US images

Procedia PDF Downloads 284