scholarly journals Modeling and Experimental Verification of Induction Heating of Thin Molybdenum Sheets

2021 ◽  
Vol 11 (2) ◽  
pp. 647
Author(s):  
Michal Frivaldsky ◽  
Miroslav Pavelek ◽  
Tibor Donic
Keyword(s):  
Induction Heating ◽  
Thermal Design ◽  
Heating Process ◽  
Operational Parameters ◽  
Fem Modeling ◽  
Operational Conditions ◽  
Geometrical Properties ◽  
Proposed Model ◽  
Set Up ◽  
Optimal Heating

This paper deals with the issues relevant for precise finite element method (FEM) modeling of thin molybdenum plates’ induction heating. The proposed methodology describes the step-by-step Multiphysics (electro-thermal) design approach, verified by the experimental measurements. Initially, it was observed that the relative error between model and experimental set-up is within the 1.2% up to 2.5% depending on the location of the measuring points. Further research was focused on the enhancement of the simulation model in the form of its parametrization. It means that it is easy to define the induction coil’s operational parameters and geometrical properties (ferrite shape, operating frequency, the distance between plate and heating element, the value of coil current, etc.). The target of this approach is to be able to determine the optimal operational settings targeting the required heating performance of thin molybdenum plates. One of the main requirements regarding the optimal heating process is temperature distribution within the molybdenum plate’s surface. The proposed model makes it possible to obtain information on optimal operational conditions based on the received results.

scholarly journals Electro-Thermal Modelling and Experimental Verification of Power Semiconductor Diode

2020 ◽  
Vol 26 (2) ◽  
pp. 48-53 ◽  
Author(s):  
Miroslav Pavelek ◽  
Michal Frivaldsky ◽  
Peter Sojka ◽  
Jan Morgos
Keyword(s):  
Simulation Model ◽  
Model Development ◽  
System Optimization ◽  
Added Value ◽  
Thermal Modelling ◽  
Semiconductor Diode ◽  
Operational Conditions ◽  
Geometrical Properties ◽  
Proposed Model ◽  
Operational Variables

The aim of the proposed paper is discussing problematics related to the thermal modelling of power electronic components. More in detail, the electro-thermal relationship is investigated for the selected power diode, while analysis shall serve for system optimization considering thermal performance with the use of highly accurate 3D simulation model. The presented approach describes the procedure of the simulation model development, whereby the main part is discussing necessities relevant for material property identification through the indirect procedure, i.e, material properties are not known from the manufacturer. Electro-thermal dependencies are defined within the proposed model, while this model enables parametric changes of the geometrical properties of the device. Added value of this procedure is the possibility of its use in exact determination of the lifetime of a semiconductor component using mathematical models taking into account operational variables (current, voltage, temperature, etc.). The proposed model is verified and validated through thermovision experimental measurements within defined operational conditions.

A numerical study of the effect of the number of turns of coil on the heat produced in the induction heating process in the 3d model

2018 ◽  
Vol 18 (3) ◽  
pp. 408-419
Author(s):  
A J shokri ◽  
M H Tavakoli ◽  
A Sabouri Dodaran ◽  
M S Akhondi Khezrabad ◽  
◽  
...  
Keyword(s):  
Induction Heating ◽  
3D Model ◽  
Numerical Study ◽  
Heating Process

scholarly journals Hydrogen Production by Fluidized Bed Reactors: A Quantitative Perspective Using the Supervised Machine Learning Approach

J ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 266-287
Author(s):  
Zheng Lian ◽  
Yixiao Wang ◽  
Xiyue Zhang ◽  
Abubakar Yusuf ◽  
Lord Famiyeh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Hydrogen Production ◽  
Fluidized Bed ◽  
Biomass Gasification ◽  
Supervised Machine Learning ◽  
Fluidized Bed Reactors ◽  
Hydrogen Yield ◽  
Carbon Conversion ◽  
Operational Parameters ◽  
Operational Conditions

The current hydrogen generation technologies, especially biomass gasification using fluidized bed reactors (FBRs), were rigorously reviewed. There are involute operational parameters in a fluidized bed gasifier that determine the anticipated outcomes for hydrogen production purposes. However, limited reviews are present that link these parametric conditions with the corresponding performances based on experimental data collection. Using the constructed artificial neural networks (ANNs) as the supervised machine learning algorithm for data training, the operational parameters from 52 literature reports were utilized to perform both the qualitative and quantitative assessments of the performance, such as the hydrogen yield (HY), hydrogen content (HC) and carbon conversion efficiency (CCE). Seven types of operational parameters, including the steam-to-biomass ratio (SBR), equivalent ratio (ER), temperature, particle size of the feedstock, residence time, lower heating value (LHV) and carbon content (CC), were closely investigated. Six binary parameters have been identified to be statistically significant to the performance parameters (hydrogen yield (HY)), hydrogen content (HC) and carbon conversion efficiency (CCE)) by analysis of variance (ANOVA). The optimal operational conditions derived from the machine leaning were recommended according to the needs of the outcomes. This review may provide helpful insights for researchers to comprehensively consider the operational conditions in order to achieve high hydrogen production using fluidized bed reactors during biomass gasification.

scholarly journals Prediction of Pest Insect Appearance Using Sensors and Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4846
Author(s):  
Dušan Marković ◽  
Dejan Vujičić ◽  
Snežana Tanasković ◽  
Borislav Đorđević ◽  
Siniša Ranđić ◽  
...  
Keyword(s):  
Machine Learning ◽  
Relative Humidity ◽  
Weather Conditions ◽  
Daily Basis ◽  
Machine Learning Algorithms ◽  
Lower Percentage ◽  
Timely Manner ◽  
Proposed Model ◽  
Set Up ◽  
Accuracy Of Prediction

The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely manner to suppress their spread. Occurrences and numbers of insects can be monitored through insect traps, which include their permanent touring and checking of their condition. Another more efficient way is to set up sensor devices with a camera at the traps that will photograph the traps and forward the images to the Internet, where the pest insect’s appearance will be predicted by image analysis. Weather conditions, temperature and relative humidity are the parameters that affect the appearance of some pests, such as Helicoverpa armigera. This paper presents a model of machine learning that can predict the appearance of insects during a season on a daily basis, taking into account the air temperature and relative humidity. Several machine learning algorithms for classification were applied and their accuracy for the prediction of insect occurrence was presented (up to 76.5%). Since the data used for testing were given in chronological order according to the days when the measurement was performed, the existing model was expanded to take into account the periods of three and five days. The extended method showed better accuracy of prediction and a lower percentage of false detections. In the case of a period of five days, the accuracy of the affected detections was 86.3%, while the percentage of false detections was 11%. The proposed model of machine learning can help farmers to detect the occurrence of pests and save the time and resources needed to check the fields.

scholarly journals The induction heating process modelling of the waveguide paths’ flanges

2021 ◽  
Vol 1047 (1) ◽  
pp. 012027
Author(s):  
A V Milov ◽  
V S Tynchenko ◽  
S O Kurashkin ◽  
V E Petrenko ◽  
D V Rogova ◽  
...  
Keyword(s):  
Induction Heating ◽  
Process Modelling ◽  
Heating Process

Enhanced photocatalytic activity of CeO2 using β-cyclodextrin on visible light assisted decoloration of methylene blue

2013 ◽  
Vol 69 (1) ◽  
pp. 113-119 ◽  
Author(s):  
Sakthivel Pitchaimuthu ◽  
Ponnusamy Velusamy
Keyword(s):  
Methylene Blue ◽  
Photocatalytic Activity ◽  
Visible Light ◽  
Inclusion Complexation ◽  
Processing Parameters ◽  
Operational Parameters ◽  
Illumination Time ◽  
Operational Conditions ◽  
Electron Microscopy Analysis ◽  
Initial Ph

An attempt has been made to enhance the photocatalytic activity of CeO2 for visible light assisted decoloration of methylene blue (MB) dye in aqueous solutions by β-cyclodextrin (β-CD). The inclusion complexation patterns between host and guest (i.e., β-CD and MB) have been confirmed with UV–visible spectral data. The interaction between CeO2 and β-CD has also been characterized by field emission scanning electron microscopy analysis. The photocatalytic activity of the catalyst under visible light was investigated by measuring the photodegradation of MB in aqueous solution. The effects of key operational parameters such as initial dye concentration, initial pH, CeO2 concentration as well as illumination time on the decolorization extents were investigated. Among the processing parameters, the pH of the reaction solution played an important role in tuning the photocatalytic activity of CeO2. The maximum photodecoloration rate was achieved at basic pH (pH 11). Under the optimum operational conditions, approximately 99.6% dye removal was achieved within 120 min. The observed results indicate that the decolorization of the MB followed a pseudo-first order kinetics.

Surveillance Models of Large-Scale ESP With High Viscosity Fluids and Gas

2012 ◽  
Author(s):  
Lissett Barrios ◽  
Stuart Scott ◽  
Charles Deuel
Keyword(s):  
Large Scale ◽  
Two Phase Flow ◽  
Electrical Current ◽  
High Viscosity ◽  
Viscous Fluids ◽  
Phase Flow ◽  
Centrifugal Pumps ◽  
Operational Parameters ◽  
Two Phase ◽  
Operational Conditions

The paper reports on developmental research on the effects of viscosity and two phases, liquid–gas fluids on ESPs which are multi stage centrifugal pumps for deep bore holes. Multiphase viscous performance in a full-scale Electrical Submersible Pump (ESP) system at Shell’s Gasmer facility has been studied experimentally and theoretically. The main objectives is to predict the operational conditions that cause degradations for high viscosity fluids when operating in high Gas Liquid Radio (GLR) wells to support operation in Shell major Projects. The system studied was a 1025 series tandem WJE 1000. The test was performed using this configuration with ten or more pump stages moving fluids with viscosity from 2 to 200 cP at various speed, intake pressure and Gas Void Fractions (GVF). For safety considerations the injected gas was restricted to nitrogen or air. The ESP system is a central artificial lift method commonly used for medium to high flow rate wells. Multiphase flow and viscous fluids causes problems in pump applications. Viscous fluids and free gas inside an ESP can cause head degradation and gas locking. Substantial attempts have been made to model centrifugal pump performance under gas-liquid viscous applications, however due to the complexity this is still a uncertain problem. The determination of the two-phase flow performance in these harmful conditions in the ESP is fundamental aspects in the surveillance operation. The testing at Shell’s Gasmer facility revealed that the ESP system performed as theoretical over the range of single flowrates and light viscosity oils up to Gas Volume Fractions (GVF) around 25%. The developed correlations predict GVF at the pump intake based on the operational parameters. ESP performance degrades at viscosity higher than 100cp as compared to light oil applications, gas lock condition is observed at gas fraction higher than 45%. Pump flowrate can be obtained from electrical current and boost for all range of GVF and speed. The main technical contributions are the analysis of pump head degradation under two important variables, high viscosity and two-phase flow inside the ESP.

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