Search results for: computational physics

Authors: Mandip Singh

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Quantum entanglement plays a fundamental role in our understanding of counter-intuitive aspects of quantum reality. If classical physics is an approximation of quantum physics, then quantum entanglement should persist at a macroscopic scale. In this paper, a thought experiment is presented where a free falling spin polarized Bose-Einstein condensate interacts with a quantum superimposed magnetic field of nonzero gradient. In contrast to the semiclassical Stern-Gerlach experiment, the magnetic field and the spin degrees of freedom both are considered to be quantum mechanical in a generalized scenario. As a consequence, a Bose-Einstein condensate can be prepared at distinct locations in space in a sense of quantum superposition. In addition, the generation of Schrodinger-cat like quantum states shall be presented.

Keywords: Schrodinger-cat quantum states, macroscopic entanglement, macroscopic quantum fields, foundations of quantum physics

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

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Authors: N. Dahbi, M. Daoudi

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This paper deals with the use of computational method based on Monte Carlo simulation in order to investigate the transport phenomena of the electron in HgCdTe narrow band gap semiconductor. Via this method we can evaluate the time dependence of the transport parameters: velocity, energy and mobility of electrons through matter (HgCdTe).

Keywords: Monte Carlo, transport parameters, HgCdTe, computational mechanics

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Authors: William J. Crowther, Conor Marsh

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Object-based flow simulation allows fast computation of arbitrarily complex aerodynamic models made up of simple objects with limited flow interactions. The proposed approach is universally applicable to objects made from arbitrarily scaled ellipsoid primitives at arbitrary aerodynamic attitude and angular rate. The use of a component-based aerodynamic modelling approach increases efficiency by allowing selective inclusion of different physics models at run-time and allows extensibility through the development of new models. Insight into the numerical stability of the model under first order fixed-time step integration schemes is provided by stability analysis of the drag component. The compute cost of model components and functions is evaluated and compared against numerical benchmarks. Model static outputs are verified against theoretical expectations and dynamic behaviour using falling plate data from the literature. The model is applied to a range of case studies to demonstrate the efficacy of its application in extensibility, ease of use, and low computational cost. Dynamically complex multi-body systems can be implemented in a transparent and efficient manner, and we successfully demonstrate large scenes with hundreds of objects interacting with diverse flow fields.

Keywords: aerodynamics, real-time simulation, low-order model, flight dynamics

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Authors: Sul-Ah Ahn, Youngim Jung

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The research activities of the computational scientists using high-performance computing are analyzed using bibliometric approaches. This study aims at providing computational scientists using high-performance computing and relevant policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of computational scientists using high-performance computing as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2006-2015. We extracted the author rank in the computational science field using high-performance computing by the number of papers published during ten years from 2006. Finally, we drew the co-authorship network for 50 top-authors and their coauthors and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.

Keywords: co-authorship network analysis, computational science, high performance computing, research activity

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Authors: Thien Van Ngo

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The engineering design process is a systematic approach to solving problems. It involves identifying a problem, brainstorming solutions, prototyping and testing solutions, and evaluating the results. The engineering design process can be used to teach students how to solve problems in a creative and innovative way. The research aim of this study was to investigate the effectiveness of using the engineering design process to enhance student learning outcomes in a physics course. A mixed research method was used in this study. The quantitative data were collected using a pretest-posttest control group design. The qualitative data were collected using semi-structured interviews. The sample was 150 first-year students in the Department of Mechanical Engineering Technology at Cao Thang Technical College in Vietnam in the 2022-2023 school year. The quantitative data were collected using a pretest-posttest control group design. The pretest was administered to both groups at the beginning of the study. The posttest was administered to both groups at the end of the study. The qualitative data were collected using semi-structured interviews with a sample of eight students in the experimental group. The interviews were conducted after the posttest. The quantitative data were analyzed using independent sample T-tests. The qualitative data were analyzed using thematic analysis. The quantitative data showed that students in the experimental group, who were taught using the engineering design process, had significantly higher post-test scores on physics problem-solving than students in the control group, who were taught using the conventional method. The qualitative data showed that students in the experimental group were more motivated and engaged in the learning process than students in the control group. Students in the experimental group also reported that they found the engineering design process to be a more effective way of learning physics. The findings of this study suggest that the engineering design process can be an effective way of enhancing student learning outcomes in physics courses. The engineering design process engages students in the learning process and helps them to develop problem-solving skills.

Keywords: engineering design process, problem-solving, learning outcome of physics, students’ physics competencies, deep learning

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Authors: Itumeleng Phage

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Students’ comprehension of graphs may be affected by the characteristics of the discipline in which the graph is used, the type of the task as well as the background of the students who are the readers or interpreters of the graph. This research study investigated these aspects of the graph comprehension of 152 first-year undergraduate physics students by comparing their responses to corresponding tasks in the mathematics and physics disciplines. The discipline characteristics were analysed for four task-related constructs namely coordinates, representations, area and slope. Students’ responses to corresponding visual decoding and judgement tasks set in mathematics and kinematics contexts were statistically compared. The effects of the participants’ gender, year of school completion and study course were determined as reader characteristics. The results of the empirical study indicated that participants generally transferred their mathematics knowledge on coordinates and representation of straight line graphs to the physics contexts, but not in the cases of parabolic and hyperbolic functions or area under graphs. Insufficient understanding of the slope concept contributed to weak performances on this construct in both mathematics and physics contexts. Discipline characteristics seem to play a vital role in students’ understanding, while reader characteristics had insignificant to medium effects on their responses.

Keywords: kinematics graph, discipline characteristics, constructs, coordinates, representations, area and slope

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Authors: T. Nagata, S. Xaphakdy, P. Souvannavong, P. Chanthamaly, K. Sithavong, C. H. Lee, S. Phommathat, V. Srithilat, P. Sengdala, B. Phetarnousone, B. Siharath, X. Chemcheng, T. Yamaguchi, A. Suenaga, S. Kashima

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National University of Laos (NUOL) requested Japan International Cooperation Agency (JICA) volunteers to begin a physics experiments class using multi media. However, there are issues. NUOL had no physics experiment class, no space for physics experiments, experiment materials were not used for many years and were scattered in various places, and there is no projector and laptop computer in the unit. This raised the question: How do authors begin the physics experiments class using multimedia? To solve this problem, the JICA took some steps, took stock of what was available and reviewed the syllabus. The JICA then revised the experiment materials to assess what was available and then developed textbooks for experiments using them; however, the question remained, what about the multimedia component of the course? Next, the JICA reviewed Physics teacher Pavy Souvannavong’s YouTube channel, where he and his students upload video reports of their physics classes at NUOL using their smartphones. While they use multi-media, almost all the videos recorded were of class presentations. To improve the multimedia style, authors edited the videos in the style of another YouTube channel, “Science for Lao,” which is a science education group made up of Japan Overseas Cooperation Volunteers (JOCV) in Laos. They created the channel to enhance science education in Laos, and hold regular monthly meetings in the capital, Vientiane, and at teacher training colleges in the country. They edit the video clips in three parts, which are the materials and procedures part including pictures, practice footage of the experiment part, and then the result and conclusion part. Then students perform experiments and prepare for presentation by following the videos. The revised experiment presentation reports use PowerPoint presentations, material pictures and experiment video clips. As for providing textbooks and submitting reports, the students use the e-Learning system of “Moodle” of the Information Technology Center in Dongdok campus of NUOL. The Korean International Cooperation Agency (KOICA) donated those facilities. The authors have passed the process of the revised materials, developed textbooks, the PowerPoint slides presented by students, downloaded textbooks and uploaded reports, to begin the physics experiments class using multimedia. This is the practice research report for beginning a physics experiments class using multimedia in the physics unit at the Department of Natural Science, Faculty of Education, at the NUOL.

Keywords: NUOL, JICA, KOICA, physics experiment materials, smartphone, Moodle, IT center, Science for Lao

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Authors: Emmanuel U. Ohaegbulem, Felix N. Nwobi

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Alternative and simple computational arrangements in carrying out multivariate profile analysis when more than two groups (populations) are involved are presented. These arrangements have been demonstrated to not only yield equivalent results for the test statistics (the Wilks lambdas), but they have less computational efforts relative to other arrangements so far presented in the literature; in addition to being quite simple and easy to apply.

Keywords: coincident profiles, g-group profile analysis, level profiles, parallel profiles, repeated measures MANOVA

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Authors: Egor Stadnichuk

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Relativistic runaway electron avalanches (RREA) are a widely accepted source of thunderstorm gamma-radiation. In regions with huge electric field strength, RREA can multiply via relativistic feedback. The relativistic feedback is caused both by positron production and by runaway electron bremsstrahlung gamma-rays reversal. In complex multilayer thunderstorm electric field structures, an additional reactor feedback mechanism appears due to gamma-ray exchange between separate strong electric field regions with different electric field directions. The study of this reactor mechanism in conjunction with the relativistic feedback with Monte Carlo simulations or by direct solution of the kinetic Boltzmann equation requires a significant amount of computational time. In this work, a theoretical approach to study feedback mechanisms in RREA physics is developed. It is based on the matrix of feedback operators construction. With the feedback matrix, the problem of the dynamics of avalanches in complex electric structures is reduced to the problem of finding eigenvectors and eigenvalues. A method of matrix elements calculation is proposed. The proposed concept was used to study the dynamics of RREAs in multilayer thunderclouds.

Keywords: terrestrial Gamma-ray flashes, thunderstorm ground enhancement, relativistic runaway electron avalanches, gamma-rays, high-energy atmospheric physics, TGF, TGE, thunderstorm, relativistic feedback, reactor feedback, reactor model

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Authors: Gabriel Ocheleka Aniedi A. Udo, Patum Wasinda

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The study was carried out to appraise the impact of ICT-based teaching methodologies (video-taped instructions and Power Point presentations) on academic performance and retention of secondary school students in Physics, with particular interest in Newton Laws of Motion. The study was conducted in Cross River State, Nigeria, with a quasi-experimental research design using non-randomised pre-test and post-test control group. The sample for the study consisted of 176 SS2 students drawn from four intact classes of four secondary schools within the study area. Physics Achievement Test (PAT), with a reliability coefficient of 0.85, was used for data collection. Mean and Analysis of Covariance (ANCOVA) was used in the treatment of the obtained data. The results of the study showed that there was a significant difference in the academic performance and retention of students taught using video-taped instructions and those taught using power point presentations. Findings of the study showed that students taught using video-taped instructions had a higher academic performance and retention than those taught using power point presentations. The study concludes that the use of blended ICT-based teaching methods can improve learner’s academic performance and retention.

Keywords: video taped instruction (VTI), power point presentation (PPT), academic performance, retention, physics

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: aerodynamics, flight control, computational fluid dynamics (CFD), flapping-wing flight

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Authors: Dana Christensen

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Undergraduate students, particularly in the environmental sciences, have difficulty displaying quantitative skills in their laboratory courses. Students spend time sampling in the field, often using new methods, and are expected to make sense of the data they collect. Computational thinking may be used to navigate these new experiences. We developed a curriculum for the marine science department at a small liberal arts college in the Northeastern United States based on previous computational thinking frameworks. This curriculum incorporates marine science data sets with specific objectives and topics selected by the faculty at the College. The curriculum was distributed to all students enrolled in introductory marine science classes as a mandatory module. Two pre-tests and post-tests will be used to quantitatively assess student progress on both content-based and computational principles. Student artifacts are being collected with each lesson to be coded for content-specific and computational-specific items in qualitative assessment. There is an overall gap in marine science education research, especially curricula that focus on computational thinking and associated quantitative assessment. The curricula itself, the assessments, and our results may be modified and applied to other environmental science courses due to the nature of the inquiry-based laboratory components that use quantitative skills to understand nature.

Keywords: marine science, computational thinking, curriculum assessment, quantitative skills

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Authors: Georgios Alexandropoulos

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The purpose of this study is to examine the historical text of Alexiad by Anna Comnena using computational tools for the extraction of lexical bundles containing the name of her father, Alexius Comnenus. For this reason, in this research we apply corpus linguistics techniques for the automatic extraction of lexical bundles and through them we will draw conclusions about how these lexical bundles serve her support provided to her father.

Keywords: lexical bundles, computational literature, critical discourse analysis, Alexiad

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Authors: Syhalath Xaphakdy, Toshio Nagata, Saykham Phommathat, Pavy Souwannavong, Vilayvanh Srithilat, Phoxay Sengdala, Bounaom Phetarnousone, Boualay Siharath, Xaya Chemcheng

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The National University of Laos (NUOL) invited a group of volunteers from the Japan International Cooperation Agency (JICA) to revise the physics experiments to utilize the materials that were already available to students. The intension was to review and revise the materials regularly utilized in physics class. The project had access to limited materials and a small budget for the class in the unit; however, by developing experimental textbooks related to mechanics, electricity, and wave and vibration, the group found a way to apply them in the classroom and enhance the students teaching activities. The aim was to introduce a way to incorporate the materials and practices in the classroom to enhance the students learning and teaching skills, particularly when they graduate and begin working as high school teachers.

Keywords: NUOL, JICA, physics experiment materials, small budget, mechanics, electricity

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: Quznetsov Gunn

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In the study of the logical foundations of probability theory, it was found that the terms and equations of the fundamental theoretical physics represent terms and theorems of the classical probability theory, more precisely, of that part of this theory, which considers the probability of dot events in the 3 + 1 space-time. In particular, the masses, moments, energies, spins, etc. turn out of parameters of probability distributions such events. The terms and the equations of the electroweak and of the quark-gluon theories turn out the theoretical-probabilistic terms and theorems. Here the relation of a neutrino to his lepton becomes clear, the W and Z bosons masses turn out dynamic ones, the cause of the asymmetry between particles and antiparticles is the impossibility of the birth of single antiparticles. In addition, phenomena such as confinement and asymptotic freedom receive their probabilistic explanation. And here we have the logical foundations of the gravity theory with phenomena dark energy and dark matter.

Keywords: classical theory of probability, logical foundation of fundamental theoretical physics, masses, moments, energies, spins

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Authors: A. E. Dumitriu

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The LHCb experiment is situated at one of the four points around CERN’s Large Hadron Collider, being a single-arm forward spectrometer covering 10 mrad to 300 (250) mrad in the bending (non-bending) plane, designed primarily to study particles containing b and c quarks. Each one of LHCb’s sub-detectors specializes in measuring a different characteristic of the particles produced by colliding protons, its significant detection characteristics including a high precision tracking system and 2 ring-imaging Cherenkov detectors for particle identification. The major two topics that I am currently concerned in are: the RIVET project (Robust Independent Validation of Experiment and Theory) which is an efficient and portable tool kit of C++ class library useful for validation and tuning of Monte Carlo (MC) event generator models by providing a large collection of standard experimental analyses useful for High Energy Physics MC generator development, validation, tuning and regression testing and V0 analysis for 2013 LHCb NoBias type data (trigger on bunch + bunch crossing) at √s=2.76 TeV.

Keywords: LHCb physics, RIVET plug-in, RIVET, CERN

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Authors: Yu Zhang, Kohei Inoue, Kiichi Urahama

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We propose a simplified bilateral filter with binarized coefficients for accelerating it. Its computational cost is further decreased by sampling pixels. This computationally low cost filter is useful for smoothing or denoising images by using mobile devices with limited computational power.

Keywords: bilateral filter, binarized-weight bilateral filter, image smoothing, image denoising, pixel sampling

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Authors: I. Turk Cakir, B. Hacisahinoglu, S. Kartal, A. Yilmaz, A. Yilmaz, Z. Uysal, O. Cakir

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In the search for new physics beyond the Standard Model, Flavour Changing Neutral Current (FCNC) is a good research field in terms of the observability at future colliders. Increased Higgs production with higher energy and luminosity in colliders is essential for verification or falsification of our knowledge of physics and predictions, and the search for new physics. Prospective electron-proton collider constituent of the Future Circular Collider project is FCC-eh. It offers great sensitivity due to its high luminosity and low interference. In this work, thq FCNC interaction vertex with off-shell top quark decay at electron-proton colliders is studied. By using MadGraph5_aMC@NLO multi-purpose event generator, observability of tuh and tch couplings are obtained with equal coupling scenario. Upper limit on branching ratio of tree level top quark FCNC decay is determined as 0.012% at FCC-eh with 1 ab ^−1 luminosity.

Keywords: FCC, FCNC, Higgs Boson, Top Quark

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Authors: Jelena Slugan, Ivica Ružić

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We are witnessing the rapid development of technologies that change the world around us. However, curriculums and teaching processes are often slow to adapt to the change; it takes time, money and expertise to implement technology in the classroom. Therefore, the University of Split, Croatia, partnered with local school Marko Marulić High School and created the project "Modern competence in modern high schools" as part of which five different curriculums for STEM areas were developed. One of the curriculums involves combining information technology with physics. The main idea was to teach students how to use different circuits and microcomputers to explore nature and physical phenomena. As a result, using electrical circuits, students are able to recreate in the classroom the phenomena that they observe every day in their environment. So far, high school students had very little opportunity to perform experiments independently, and especially, those physics experiment did not involve ICT. Therefore, this project has a great importance, because the students will finally get a chance to develop themselves in accordance to modern technologies. This paper presents some new methods of teaching physics that will help students to develop experimental skills through the study of deterministic nature of physical laws. Students will learn how to formulate hypotheses, model physical problems using the electronic circuits and evaluate their results. While doing that, they will also acquire useful problem solving skills.

Keywords: ICT in physics, curriculum, laboratory activities, STEM (science, technology, engineering, mathematics)

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Authors: A. Metioui

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Research related to the student’s conceptual difficulties in sciences, particularly in the field of physics, are relatively numerous. In this work, we will analyze the results of qualitative research conducted with 80 elementary preservice teachers from Quebec in Canada on their understandings after studying the free fall bodies. First, we will illustrate the paper-pencil questionnaire built for this purpose. Then we will give the analysis of the experimental data. The results show that, even though there is a continuing physics education, many misconceptions persist despite the teaching provided.

Keywords: pre-service teachers, elementary school, conceptual difficulties, free fall bodies

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Authors: Baldev Ram Khandoliyan, Ram Kishor

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India has a classical tradition of Sanskrit Lexicons. Research work has been done on the study of Indian lexicography. India has seen amazing strides in Information and Communication Technology (ICT) applications for Indian languages in general and for Sanskrit in particular. Since Machine Translation from Sanskrit to other Indian languages is often the desired goal, traditional Sanskrit lexicography has attracted a lot of attention from the ICT and Computational Linguistics community. From Nighaŋţu and Nirukta to Amarakośa and Medinīkośa, Sanskrit owns a rich history of lexicography. As these kośas do not follow the same typology or standard in the selection and arrangement of the words and the information related to them, several types of Kośa-styles have emerged in this tradition. The model of a grammar given by Aṣṭādhyāyī is well appreciated by Indian and western linguists and grammarians. But the different models provided by lexicographic tradition also have importance. The general usefulness of Sanskrit traditional Kośas is well discussed by some scholars. That is most of the matter made available in the text. Some also have discussed the good arrangement of lexica. This paper aims to discuss some more use of the different models of Sanskrit lexicography especially focusing on its computational modeling and its use in different computational operations.

Keywords: computational lexicography, Sanskrit Lexicons, nighanṭu, kośa, Amarkosa

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Authors: Jatinder Kumar, Ajay Bansal

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Simulation of a photocatalytic reactor helps in understanding the complex behavior of the photocatalytic degradation. Simulation also aids the designing and optimization of the photocatalytic reactor. Lack of simulation strategies is a huge hindrance in the commercialization of the photocatalytic technology. With the increased performance of computational resources, and development of simulation software, computational fluid dynamics (CFD) is becoming an affordable engineering tool to simulate and optimize reactor designs. In the present paper, a CFD (Computational fluid dynamics) model for simulating the performance of an immobilized-titanium dioxide based annular photocatalytic reactor was developed. The computational model integrates hydrodynamics, species mass transport, and chemical reaction kinetics using a commercial CFD code Fluent 6.3.26. The CFD model was based on the intrinsic kinetic parameters determined experimentally in a perfectly mixed batch reactor. Rhodamine B, a complex organic compound, was selected as a test pollutant for photocatalytic degradation. It was observed that CFD could become a valuable tool to understand and improve the photocatalytic systems.

Keywords: simulation, computational fluid dynamics (CFD), annular photocatalytic reactor, titanium dioxide

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Authors: Tai Yuan Yu, Pei-Jen Wang

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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings, abbreviated as GFBs, are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional, abbreviated as 3D, fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: fluid-structure interaction, multi-physics simulations, gas foil bearing, oil-free, transient thermo-hydrodynamic

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Authors: Edson Pierre, Gustavo de Jesus Lopez Nunez

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The objective of this work is to analyze how physics can be taught remotely through the use of platforms and software to attract the attention of 2nd-year high school students at Colégio Cívico Militar Professor Carmelita Souza Dias and point out how remote teaching can be a teaching-learning strategy during the period of social distancing. Teaching physics has been a challenge for teachers and students, permeating common sense with the great difficulty of teaching and learning the subject. The challenge increased in 2020 and 2021 with the impact caused by the new coronavirus pandemic (Sars-Cov-2) and its variants that have affected the entire world. With these changes, a new teaching modality emerged: remote teaching. It brought new challenges and one of them was promoting distance research experiences, especially in physics teaching, since there are learning difficulties and it is often impossible for the student to relate the theory observed in class with the reality that surrounds them. Teaching physics in schools faces some difficulties, which makes it increasingly less attractive for young people to choose this profession. Bearing in mind that the study of physics is very important, as it puts students in front of concrete and real situations, situations that physical principles can respond to, helping to understand nature, nourishing and nurturing a taste for science. The use of new platforms and software, such as PhET Interactive Simulations from the University of Colorado at Boulder, is a virtual laboratory that has numerous simulations of scientific experiments, which serve to improve the understanding of the content taught practically, facilitating student learning and absorption of content, being a simple, practical and free simulation tool, attracts more attention from students, causing them to acquire greater knowledge about the subject studied, or even a quiz, bringing certain healthy competitiveness to students, generating knowledge and interest in the themes used. The present study takes the Theory of Social Representations as a theoretical reference, examining the content and process of constructing the representations of teachers, subjects of our investigation, on the evaluation of teaching and learning processes, through a methodology of qualitative. The result of this work has shown that remote teaching was really a very important strategy for the process of teaching and learning physics in the 2nd year of high school. It provided greater interaction between the teacher and the student. Therefore, the teacher also plays a fundamental role since technology is increasingly present in the educational environment, and he is the main protagonist of this process.

Keywords: physics teaching, technologies, remote learning, pandemic

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Authors: Yogesh D. Bansod, Jiri Bursa

Abstract:

The quantitative study of cell mechanics is of paramount interest since it regulates the behavior of the living cells in response to the myriad of extracellular and intracellular mechanical stimuli. The novel experimental techniques together with robust computational approaches have given rise to new theories and models, which describe cell mechanics as a combination of biomechanical and biochemical processes. This review paper encapsulates the existing continuum-based computational approaches that have been developed for interpreting the mechanical responses of living cells under different loading and boundary conditions. The salient features and drawbacks of each model are discussed from both structural and biological points of view. This discussion can contribute to the development of even more precise and realistic computational models of cell mechanics based on continuum approaches or on their combination with microstructural approaches, which in turn may provide a better understanding of mechanotransduction in living cells.

Keywords: cell mechanics, computational models, continuum approach, mechanical models

Procedia PDF Downloads 353

Authors: S. A. Sadegh Zadeh, C. Kambhampati

Abstract:

Mathematical and computational modellings are the necessary tools for reviewing, analysing, and predicting processes and events in the wide spectrum range of scientific fields. Therefore, in a field as rapidly developing as neuroscience, the combination of these two modellings can have a significant role in helping to guide the direction the field takes. The paper combined mathematical and computational modelling to prove a weakness in a very precious model in neuroscience. This paper is intended to analyse all-or-none principle in Hodgkin-Huxley mathematical model. By implementation the computational model of Hodgkin-Huxley model and applying the concept of all-or-none principle, an investigation on this mathematical model has been performed. The results clearly showed that the mathematical model of Hodgkin-Huxley does not observe this fundamental law in neurophysiology to generating action potentials. This study shows that further mathematical studies on the Hodgkin-Huxley model are needed in order to create a model without this weakness.

Keywords: all-or-none, computational modelling, mathematical model, transmembrane voltage, action potential

Procedia PDF Downloads 603

Authors: Paul Stonaha, Mariia Romashchenko, Xaio Xu

Abstract:

Magnetic shape memory alloys (MSMAs) are promising technological materials for a range of fields, from biomaterials to energy harvesting. We have performed inelastic neutron scattering on two powder samples of cobalt-based high-entropy MSMAs across a range of temperatures in an effort to compare calculations of thermodynamic properties (entropy, specific heat, etc.) to the measured ones. The measurements were correct for multiphonon scattering and multiple scattering contributions. We present herein the neutron-weighted vibrational density of states. Future work will utilize DFT calculations of the disordered lattice to correct for the neutron weighting and retrieve the true thermodynamical properties.

Keywords: neutron scattering, vibrational dynamics, computational physics, material science

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