Vibration response of Euler-Bernoulli-damped beam with appendages subjected to a moving mass

This paper addresses the problem of a viscoelastic Euler-Bernoulli beam under the influence of a constant velocity moving mass and different types of appendages.Four types of boundary conditions are considered:pinned-pinned,fixed-pinned,fixed-free(or cantilever),and fixed-fixed.Appendages considered include lumped masses,dampers,and springs.The modal decomposition method is employed to derive the equation of motion of the beam,for which an analytical closed-form expression of the dynamic vibration response is generated.The proposed method enables the study of the effect of a single appendage or a combination of the three types of appendages on the non-dimensional dynamic response of the beam.Numerical examples are presented to illustrate the effects of these appendages and compare them to the reference cases of a beam with no appendages.The results demonstrate the importance of considering these parameters in the design of structures.The proposed method is compared to other techniques in the literature and found to be advantageous due to its direct approach.The method also offers a versatile tool for investigating various configurations,aiding in engineering design and structural analysis for which establishing a precise prediction of beam vibrations is crucial.

A Novel Method for Thermoelectric Generator Based on Neural Network

The growing need for renewable energy and zero carbon dioxide emissions has fueled the development of thermoelectric generators with improved power generating capability.Along with the endeavor to develop thermoelectric materials with greater figures of merit,the geometrical and structural optimization of thermoelectric generators is equally critical for maximum power output and efficiency.Green energy strategies that are constantly updated are a viable option for addressing the global energy issue while also protecting the environment.There have been significant focuses on the development of thermoelectric modules for a range of solar,automotive,military,and aerospace applications in recent years due to various advantages including as low vibration,great reliability and durability,and the absence of moving components.In order to enhance the system performance of the thermoelectric generator,an artificial neural network(ANN)based algorithm is proposed.Furthermore,to achieve high efficiency and system stability,a buck converter is designed and deployed.Simulation and experimental findings demonstrate that the suggested method is viable and available,and that it is almost similar to the real value in the steady state with the least power losses,making it ideal for vehicle exhaust thermoelectric generator applications.Furthermore,the proposed hybrid algorithm has a high reference value for the development of a dependable and efficient car exhaust thermoelectric generating system.

Optimal Allocation of STATCOM to Enhance Transient Stability Using Imperialist Competitive Algorithm

With the daily expansion of global energy consumption,developing the power grids is of uttermost importance.However,building a new trans-mission line is costly and time-consuming,so utilizing the same lines with possible higher transmission capacity is very cost-effective.In this regard,to increase the capacity of the transmission lines,the flexible alternating current transmission system(FACTS)has been widely used in power grids in recent years by industrialized countries.One of the essential topics in electrical power systems is the reactive power compensation,and the FACTS plays a significant role in controlling the reactive power current in the power grid and the system voltage oscillations and stability.When a static synchronous compensator(STATCOM)is embedded in a power system to increase the bus voltage,a supplementary damping controller can be designed to enhance the system oscillation damping.Given the expansion of the grids in the power system,the complexity of their optimization and the extraordinary ability of the imperialist competitive algorithm(ICA)for solving such problems,in this paper,the ICA has been used to determine the optimal position and size of the FACTS devices.

The use of facial expressions in measuring students’interaction with distance learning environments during the COVID-19 crisis

Digital learning is becoming increasingly important in the crisis COVID-19 and is widespread in most countries.The proliferation of smart devices and 5G telecommunications systems are contributing to the development of digital learning systems as an alternative to traditional learning systems.Digital learning includes blended learning,online learning,and personalized learning which mainly depends on the use of new technologies and strategies,so digital learning is widely developed to improve education and combat emerging disasters such as COVID-19 diseases.Despite the tremendous benefits of digital learning,there are many obstacles related to the lack of digitized curriculum and collaboration between teachers and students.Therefore,many attempts have been made to improve the learning outcomes through the following strategies:collaboration,teacher convenience,personalized learning,cost and time savings through professional development,and modeling.In this study,facial expressions and heart rates are used to measure the effectiveness of digital learning systems and the level of learners’engagement in learning environments.The results showed that the proposed approach outperformed the known related works in terms of learning effectiveness.The results of this research can be used to develop a digital learning environment.

Corrigendum to“The Use of Facial Expressions in Measuring Students’Interaction with Distance Learning Environments During the COVID-19 Crisis”Visual Informatics,Volume 7,Issue 1,March 2023,Pages 1–17

The authors regret that they missed to add the fourth author Abdallah Altahan Alnuaimi who contributed to this paper in formalizing the research methodology.His affiliation details and email address are as below。