Virtual Material Research Articles

Development of Learning Materials Making Virtual Learning-Based Videos Community Local Wisdom Through Learning Experience for Students

Abstract: The effectiveness of learning through virtual media is increasingly achieving its goals if lecturers and students can develop instructional video media as virtual learning materials. The use of instructional videos in the learning process needs to be systematically designed so that learning media can be used effectively, experience learning-based learning videos so that they are more contextual about the local wisdom of the community. The research objective was to produce a learning model and learning materials for the development of virtual learning video media based on local wisdom of the community through learning experience for students of the Department Non-Formal Education, Faculty of Education, State University of Malang. The research method used is the development (research development) development research model is an attempt to develop and validate educational products. The research design is systematical as follows: (1) the stage of analyzing, (2) the writing stage, (3) the stage of expert assessment and revising, and (4) the stage of the limited trial of the readability of the contents of learning materials related to understanding the content. The conclusion is based on the data analysis of the results of the content assessment on the development of learning materials for making virtual learning video media based on local wisdom of the community through a learning experience in the subject of learning resources and learning media department non-formal educations obtained valid results.

Kitchen Matters: Virtual materials science outreach through food and cooking

The kitchen is our best home laboratory. Inspired by this, we launched Kitchen Matters, a new outreach program that uses home cooking experiments to explore materials science. After a year of virtual outreach, we reflect on making materials science come alive, even with our audience half a world away.

Optimalisasi Penggunaan Aplikasi Whatsapp dan Google Meet Dalam Pembelajaran Masa Pandemi Covid-19

Learning during the pandemic covid-19 is done online. Learning media based on information technology in the form of electronic learning can be used as a solution to the learning process during the pandemic covid-19.This study aims to analyze the use of whatsaap and google meet applications as optimization of online learning during the pandemic covid-19.This research is library research because all the data is sourced from library materials, books, articles, research journals, and documents relevant to the focus of research.This research revealed that collaboration of the use of whatsapp and google meet applications can help in the learning process, the use of whatsapp group can be enabled to send material files and the use of google meet can be enabled for virtual learning process, material delivery and question and answer discussion.

An Overview of Online Resources for Medical Spanish Education for Effective Communication with Spanish-Speaking Patients

Phenomenon Despite the rapid development of virtual medical Spanish educational materials, online resources lack transparency and a peer-review process. The purpose of this interdisciplinary study was to provide a critical inventory of virtual resources for medical Spanish education, thereby providing a panorama of the current state of online medical Spanish. Approach Research team members conducted iterative searches to identify medical Spanish online resources, which were then screened for predetermined inclusion/exclusion criteria. Between June and August 2020, a panel of medical and language experts then adapted and applied a previously published evaluation tool to determine whether resources that met study criteria would help learners achieve medical Spanish core competencies and to what extent each resource incorporated communicative language activities. Consensus meetings were conducted to resolve disagreements and identify gaps in online education. Findings Out of 465 resources, 127 were further screened, and eight were selected for evaluation. Medical and language specialists independently scored each resource and, following discussions, achieved consensus. Overall, no resource met suitability criteria for all five medical Spanish learner competencies or cultural elements, and only one was suitable for achieving the self-assessment competency. Insights Interdisciplinary consensus meetings provide an important avenue for resolving differences of opinion and for integrating both language and medical perspectives into the evaluation process. Existing online resources should be used in conjunction with other materials to ensure that all core competencies for medical Spanish education are addressed. This study revealed important gaps in online resources, including a need to target advanced Spanish learners, apply authentic communicative activities, include assessment opportunities, and integrate culture in the learning program. Based on the current state of online medical Spanish, we offer recommendations for future resources.

Analysis on the Application Prospect of Virtual Reality Technology and Material in Physical Education

With the update and growth of science and technology, educational concepts continue to innovate. In the sports field, the use of Virtual Reality (VR) technology is undoubtedly a brand new training experience. The use of VR technology in the physical education (PE) classroom has promoted the growth of PE and also allowed students to master physical skills more comprehensively through high technology. The purpose of this article is to understand VR technology, study the mterial of VR, improve the shortcomings of traditional PE through VR technology, and analyze the application prospects of VR technology in PE. This article mainly adopts the interview method, sample survey method and case analysis method to sample a survey of 120 students in three grades of a middle school to conduct questionnaire surveys and field visits to understand the students’ knowledge of VR technology and the use of VR technology. We also can know the views of the PE for students. Through this series of investigations, the prospects of VR technology being applied to PE are analyzed. Experimental research results show that the most supported PE activity for VR technology at this stage is situational setting, and 35% of students hope that VR technology will be prominent in the context of the picture. The application of VR technology in physical education will undoubtedly bring a different experience to school sports activities. However, due to the lack of funds and professionals, it is difficult to carry out VR technology in teaching activities. So we can start from the context setting and use economical means to pave the way for physical education.

O46 Social Media Use of West Virginia Community Programs Participants to Inform Online Health Educational Programming

<h3>Background</h3> Internet usage has increased dramatically over the past 15 years, with many health and nutrition education programming transitioning online or using social media, including Supplemental Nutrition Assistance Programs (SNAP). This creates potential barriers for rural and low-income populations who have limited access to internet coverage when compared to urban areas. Therefore, it is important to understand how low-income, rural SNAP participants use the internet, including social media, to best determine methods in delivering virtual health-education materials. <h3>Objective</h3> The objective of this study was to investigate the social media usage of low-income, rural SNAP participants to determine best methods to deliver health-education materials. <h3>Study Design, Setting, Participants</h3> Participants of the Expanded Food and Nutrition Program in serval counties of West Virginia completed a cross-sectional survey that collected data on their internet access and social media use. <h3>Measurable Outcomes/Analysis</h3> Frequency of responses and contingency analyses were conducted to determine social media use by various subgroups. <h3>Results</h3> Respondents (n = 158) were primarily female (68.1%), aged 25-34 (28.1%), did not receive SNAP, WIC, or TANF benefits (56.4%), and were not pregnant or with children in the home (60.6%). The majority had a smartphone (87.5%), reliable cell service at home (85.5%), reliable internet at home (80.9%), and used their smartphone to access the internet (78.1%). The most commonly used Facebook (82.5%) and YouTube (61.3%), in which participants sought videos for musical or educational purposes. Those who received SNAP benefits used Facebook (<i>P</i> = 0.013) and YouTube (<i>P</i> = 0.044) more often and Twitter (<i>P</i> = 0.0459) less often than those who did not receive SNAP benefits. <h3>Conclusion</h3> The use of social media platforms varied depending on age, gender, SNAP participation and having dependents. These results show the need to gear online health educational programs for SNAP recipients to certain media platforms such as Facebook and YouTube as modes of delivery.

Assessment of Technological Setup for Teaching Real-Time and Recorded Laboratories for Online Learning: Implications for the Return to In-Person Learning

Lab-based learning is an essential part of any undergraduate chemistry curriculum as it incorporates necessary and required hands-on experiential learning. However, in response to the COVID-19 pandemic, many students are learning from home, rendering laboratory instruction a particular challenge. Options for educators include third party virtual and prerecorded materials, at-home laboratory experiments, and original prerecorded and real-time instruction. Here, we report the assessment of a variety of technological setups for real-time and prerecorded original content looking at a variety of audio and video sources as well as one-camera and two-camera options. We intentionally selected equipment that we had readily available and ensured our recordings were as close to the student experience as possible by recording via a secondary computer signed into an online learning platform. Upon a survey of a small group of students at Quest University Canada, we found that 72% of students preferred a two-camera setup using a smartphone to film the instructor as a whole and a web camera to provide a close-up view of the chemistry taking place. This setup was used for a diversity of real-time and prerecorded experiments delivered remotely at Quest University including titrations, basic synthetic reactions, and purifications. For two of the experiments, a titration lab and a synthesis and purification lab, we assessed the ability of different remote learning options to meet pre-COVID-19 learning outcomes. Real-time, digital laboratory instruction is clearly the most effective. In addition, we suggest scenarios where using digital techniques may create efficiencies in laboratory teaching upon the return to on-campus learning.

Criterion for Imminent Failure During Loading—Discrete Element Method Analysis

It has recently been reported that the equal load sharing fiber bundle model predicts the rate of change of the elastic energy stored in the bundle reaches its maximum before catastrophic failure occurs, making it a possible predictor for imminent collapse. The equal load sharing fiber bundle model does not contain central mechanisms that often play an important role in failure processes, such as localization. Thus, there is an obvious question whether a similar phenomenon is observed in more realistic systems. We address this question using the discrete element method to simulate breaking of a thin tissue subjected to a stretching load. Our simulations confirm that for a class of virtual materials which respond to stretching with a well-pronounced peak in force, its derivative and elastic energy we always observe an existence of the maximum of the elastic energy change rate prior to maximum loading force. Moreover, we find that the amount of energy released at failure is related to the maximum of the elastic energy absorption rate.

A virtual materials testing approach to calibrate anisotropic yield functions for the simulation of earing during deep drawing of aluminium alloy sheet

We present a pragmatic and computationally efficient scheme to combine polycrystal-plasticity models based on crystallographic texture with phenomenological yield functions into a multilevel modelling framework for consideration of the anisotropic materials response during finite-element (FE) simulations of forming operations. Materials tests are conducted virtually using the visco-plastic self-consistent (VPSC) polycrystal-plasticity model to provide the stresses and strain ratios in uniaxial tension, plane-strain tension and under balanced biaxial conditions. These anisotropic materials data are then utilized to calibrate an advanced phenomenological yield function, viz. Yld2011–27p due to Aretz and Barlat, to simulate the anisotropic materials behaviour during subsequent sheet metal forming operations, here, deep-drawing. Since the simulated materials data can be used just as experimental values, no special fitting procedure for the yield function is required and validation of the simulation results is straightforward. Moreover, the followed modelling scheme enables to combine materials data obtained from experimental and virtual tests in a so-called hybrid approach. The modelling scheme was validated by FE-simulations of the earing behaviour of various Al sheet alloys, including AA 1200-O, AA 3104-H19, AA 5182-O and AA 5050A-H44, with distinctively different textures. Since earing is almost entirely controlled by crystallographic texture, analysis of the earing behaviour provides for a meaningful but demanding proof-of-principle for the current hierarchical modelling scheme.

Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine Learning.

Organic semiconductors are indispensable for today's display technologies in the form of organic light-emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long timescales are required, which is the case to compute static and dynamic energy disorder, i.e., the dominant factor to determine charge transport. Here, we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps are highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyze characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application-relevant materials properties of organic semiconductors and thus make these methods applicable for virtual materials design.

An Efficient Multi-Scale Modeling Method that Reveals Coupled Effects Between Surface Roughness and Roll-Stack Deformation in Cold Sheet Rolling

Abstract In thin-gauge cold rolling of metal sheet, the surface roughness of work rolls (WRs) is known to affect the rolled sheet surface morphology, the required rolling load, and the roll wear. While modeling of rough surfaces using statistical asperity theory has been widely applied to problems involving semi-infinite solids, the application of asperity distributions and their elastic-plastic behavior has not been considered in roll-stack models for cold sheet rolling. In this work, a simplified-mixed finite element method (SM-FEM) is combined with statistical elastic-plastic asperity theory to study contact interference and coupling effects between a rough work roll (WR) surface and the roll-stack mechanics in cold sheet rolling. By mixing equivalent rough surface contact foundations, Hertz foundations, and Timoshenko beam stiffness, an approach is created to efficiently model interactions between the micro-scale asperities and the macro-scale roll-stack deformation. Nonlinearities from elastic-plastic material behavior of the asperities and the sheet, as well as changing contact conditions along the roll length, are also accommodated. Performance of the multi-scale SM-FEM approach is made by comparison with a continuum finite element virtual material model. 3D studies for a 4-high mill reveal new multi-scale coupling behaviors, including nonuniform roughness transfer, and perturbations to the sheet thickness “crown” and contact force profiles. The described multi-scale SM-FEM approach is general and applies to rough surface contact problems involving plates and shear-deformable beams having multiple contact interfaces and arbitrary surface profiles.

Development of Educational Virtual Reality Teaching Materials in Small Animal Practice for Veterinary Students

Development of Educational Virtual Reality Teaching Materials in Small Animal Practice for Veterinary Students

Finite Element Analysis Based on Virtual Material and Experimental of Vacuum Chamber

Electron beam imaging system plays an important role in chip defect detection, so optimizing its dynamic performance is crucial. To understand the vibration characteristics of the electron beam imaging system, a reasonable finite element model is established. The simulation results show that the natural frequencies of the model adding virtual material layer are more accurate than bounded, but the local mode caused by the virtual material layer needs to be eliminated. The error of this method is within 10%, which verifies the accuracy of virtual materials in large assemblies. Our research promotes the development of the chip inspection technology.

Critical Load Prediction in Notched E/Glass-Epoxy-Laminated Composites Using the Virtual Isotropic Material Concept Combined with the Average Strain Energy Density Criterion.

This paper attempts to validate the application of the Virtual Isotropic Material Concept (VIMC) in combination with the average strain energy density (ASED) criterion to predict the critical load in notched laminated composites. This methodology was applied to E/glass–epoxy-laminated composites containing U-notches. For this purpose, a series of fracture test data recently published in the literature on specimens with different notch tip radii, lay-up configurations, and a number of plies were employed. It was shown that the VIMC–ASED combined approach provided satisfactory predictions of the last-ply failure (LPF) loads (i.e., critical loads).

Mixed mode I/II crack propagation in stainless steel 316L sheets by large plastic deformations: Prediction of critical load by combining LEFM with fictitious material concept

In this research, the load carrying capacity (LCC) of O-notched diagonally loaded square plate (DLSP) samples with pre-existing cracks emanating from the notch edge is investigated theoretically and experimentally under mixed mode I/II loading. The specimens are made of the stainless steel 316L, which is highly ductile and has great strain-hardening. In order to determine the LCC experimentally, several fracture tests are performed on DLSP specimens. Experimental observations reveal that these specimens experience significant plastic deformations at the onset of crack propagation. For theoretical prediction of the experimental LCCs, the Fictitious Material Concept (FMC) is first employed. By utilizing FMC, the stainless steel 316L with highly ductile behavior and great strain-hardening can be replaced with a virtual brittle material having linear elastic behavior. Then, by coupling FMC with two well-known stress based brittle fracture criteria in the field of the linear elastic fracture mechanics (LEFM), the LCCs of the cracked DLSP samples are estimated. In fact, by using FMC, complex and time-consuming elastoplastic failure analysis can be avoided and by performing only linear elastic analysis, the LCC of ductile DLSP specimens can be estimated. It is shown that combination of FMC with the maximum tangential stress (MTS) and the generalized MTS (GMTS) criteria is quite successful in predicting the crack growth instance in ductile DLSP specimens.

Affectual Dramaturgy for Augmented Reality Immersive Heritage Performance

This paper introduces the concept of Affectual Dramaturgy as a lens for creating digitally mediated immersive performances in the context of cultural heritage. In doing so we bring together two disciplines, smartglass Augmented Reality design (AR) and immersive heritage performance, with the aim to innovate experiences built for heritage sites.For both disciplines, immersive experience building uses interactive methods to engage the public with the tangible and intangible heritage of a site. Immersive heritage performance incorporates narrative-led, affective, and ludic techniques found in virtual and live immersive and participatory theatre practice. Smartglass AR experiences communicate to the viewer how a place was in the past by means of superimposing on the physical space virtual material accompanied with audio.However, often, the orchestration of the virtual material does not take the context into account and the superimposition of digital information misses an opportunity to connect into the existing narrative of the site tapping into its rich dramatic potential. This article explores how AR design and live performance can blend together through embodied storytelling techniques designed to draw the public’s attention to their sensorial experience of the site, and offer them a deeper understanding of the place’s history, which we refer to as affectual dramaturgy. By fusing embodied, affectual, and sensorial experience into the public’s engagement with the site, this article explores how interdisciplinary collaborations between theatre and AR design may create innovative tools and methods to tell stories of the past for the 21st century museums.

Effective stiffness and thermal expansion of three-phase multifunctional polymer electrolyte coated carbon fibre composite materials

Multifunctional composites including polymer electrolyte coated carbon fibres and polymer matrix systems gained recent interest in light-weight design related research areas. Compared to classical fibre reinforced plastics, the interphase, made by electropolymerisation on the fibre surface, represents a new, third material phase. The coating serves as ion-conducting separator in structural batteries and as insulating layer in energy transmitting multifunctional composites. The importance of this study is related to the fact, that multifunctional applications, based on such composites, are exposed to temperature changes in many cases. The coating material, acting as thin interphase, shows a significant temperature dependant Young’s modulus, determining the overall macroscopic behaviour under thermal loads. The new influences on the effective elastic properties of the composite are determined in this work in a 3D microstructural simulation approach based on a unit cell geometry. For the first time, the resulting effective properties are discussed towards the state of research and future work. First, the effective elastic stiffness is computed by isothermal virtual material testing, applying unit strain modes on the unit cell. Second, a uniform temperature change is applied and the effective thermal expansion coefficients are computed. The results show that a change of stiffness in the coating domain has a great influence on the effective stiffness in the transversal isotropic plane. The effective thermal expansion of the composite is also highly sensitive to the thermal expansion behaviour of the coating phase. Main conclusions are drawn towards multiphysical material simulation: Influences of the coating material properties have to be taken into account to compute effective properties. In particular, it is necessary to include the temperature dependant stiffness and the coefficients of thermal expansion of the interphase, which affect effective properties significantly. A thermo-mechanic coupled microscale model is needed to represent in-situ properties of such composites for applications with heat exposure.

Wood fiber modelling using stochastic models

Various kinds of materials such as iron, wood, and concrete are very useful in human life. For example, the wood fiber can be used in building construction such as wall, roof, floor, as well as automotive interior. The design process of such materials is therefore still continuously researched and developed in order to create high quality products. To avoid excessive costs, it is essential to establish a non-destructive design technique of the macroscopic material. In this paper, the design technique of fibrous material using computer based modelling (virtual material design) as the realization of stochastic models will be investigated. In this model, the fiber can be stated as either a dilated curved lines, a chain of balls or cylinders with different cross-section. In this research, we will focus to investigate the image of Medium Density Fiber (MDF). It will be modelled as cylinders using the Poisson cylinder process with a rectangular cross-section. We also use Euler rotation and β-distribution to determine the position and orientation of the fibers in the system. Simulation software was conducted to verify the model. The result showed that the realization of fibers model is similar to the image of the wood fibers sample.

A construction method of digital twin model for contact characteristics of assembly interface

The paper aims to study the accurate modeling of the assembly interface and the update of the digital twin model to keep the consistency of physical and digital information. It purposes a construction method of the digital twin model of assembly interface contact characteristics, based on the interface virtual thin-layer element with nonuniform and replaceable attribute parameters. Firstly, the general framework of the digital twin model of assembly interface contact characteristics is given. Secondly, the typical assembly interface characteristics are analyzed. Aiming at the precise modeling of the assembly interface, the interface gradient virtual material thin-layer element is developed by integrating the measured data. Based on the surrogate model and genetic algorithm, the real-time assimilation and fusion of test data and simulation data are carried out. The thin-layer element parameters are optimized, and the dynamic updating of the assembly digital twin model is realized. Finally, the twin data model is applied to the dynamic performance analysis of the machining center and compared with the Takashi Yoshimura method. The results show that the analysis results of the twin data model are in good agreement with the test data, and the analysis accuracy is higher than that of the Takashi Yoshimura method, which verifies the feasibility of the digital twin model modeling method for assembly contact characteristics. The twin data model of contact characteristics can be extended and used to predict the mechanical performance of multiple joint structures in real time.

Stochastic 3D microstructure modeling of anodes in lithium-ion batteries with a particular focus on local heterogeneity

Lithium-ion batteries can be considered as one of the most important energy storing devices. To satisfy the rapidly growing demand for higher energy densities, as for example required by automotive applications, the optimization of the electrode morphology is an important goal in battery research since it is well known that the 3D microstructure of anodes and cathodes has a significant impact on the resulting performance of the battery. A promising approach is called virtual materials testing, where stochastic 3D microstructure models are used to generate a wide range of virtual but realistic electrode morphologies as structural input for spatially-resolved numerical simulations of effective electrochemical properties. This beneficial combination allows to derive microstructure–property relationships just at the cost of computer simulations. The present paper introduces a novel parametric stochastic 3D microstructure model based on random fields that is calibrated to tomographic image data of six graphite anodes. The model is validated by comparing geometrical characteristics and effective tortuosity, which significantly influences the electrochemical behaviour of battery electrodes, computed for tomographic and simulated image data, respectively. A particular focus is put on local heterogeneity, which is quantitatively accessed by computing local distributions of certain microstructure-dependent descriptors.