Effects Of Physical Models Research Articles

Numerical simulation of an industrial radiant tube burner using OpenFOAM

This study presents a numerical investigation into the effects of physical models on the prediction accuracy of the wall temperature distribution in an industrial radiant tube burner. Utilizing a reacting flow solver based on OpenFOAM, we explored the effects of various physical models, including those for chemistry, combustion, heat transfer, and radiation properties. The choice of combustion model significantly influences prediction accuracy, playing a more dominant role than the chemistry mechanism. Moreover, the simulations captured a distinctive triple flame structure inside the burner, representing the coexistence of rich premixed, non-premixed, and lean premixed flame structures. Conditional scatter plots displayed the development of both premixed and non-premixed flame structures, converging on the fuel-lean side. Notably, accurate prediction of wall temperature distribution depends on the incorporation of a precise heat transfer model, coupled with a detailed radiation property model. Regarding the distribution of tube surface temperature in the main radiation zone (a distance from the burner nozzle greater than 1 m), the most accurate prediction exhibits a maximum deviation of less than 56 K and an average deviation of 24 K compared to experimental results. The simulation closely matched experimental data for exhaust concentration of NO within an error margin of 20 ppm. However, discrepancy was observed in the CO concentration, which was attributed to the simplified representations of fuel chemistry and composition, as well as the difficulties in accurately capturing the unsteady flame dynamics near the wall.

Effects of physical models and simulations to understand daily life applications of electromagnetic induction

Background: One of the topics students have difficulties in understanding is electromagnetic induction. Active learning methods instead of traditional learning method may be able to help facilitate students’ understanding such topics more effectively.Purpose: The study investigated the effectiveness of physical models and simulations on students’ understanding daily life applications of electromagnetic induction.Sample: The nine participants in the study were voluntaries from the fourth year of the physics education undergraduate programme.Design and methods: Lessons were designed to enhance students’ conceptual understanding of electromagnetic induction. Researchers developed multiple generator and simple electric motor models. These models and simulations about Faraday’s Law, magnetic field, magnets, generator and radio waves were used in lessons. The data were collected through open-ended questionnaire and semi-structured interview. Open-ended questionnaire was employed in a pre-test and a post-test. Students’ answers were categorized as sound understanding, partial understanding, misunderstanding and no understanding. At the end of the last lesson, the interview was implemented about the students’ opinions related to application.Results: For each question, the number of responses matching the accepted scientific explanation increased after application. The number of illogical or incorrect responses decreased.Conclusions: Physical models and simulations used in the present study had positive effect on students participated in this study to understand electromagnetic induction and its daily life applications.

Simulation on Boron Concentration Profile in Silicon Introduced by Plasma Doping

Plasma doping (PD) is a potential shallow junction technology for advanced integrated circuits manufacturing. Accurate simulation on PD is thus needed. The simulation on PD induced B concentration profile in Si is presented in this paper. A computational efficiency Molecular Dynamics (MD) method is applied. The plasma potential, the deviation of ion energy, and the injection angle are considered. The effect of physical models, including different ion species, threshold energy of displacement, energy variation model, electronic stopping model, is investigated. It is demonstrated that the proper agreement between simulation results and experimental data can be achieved for PD.