Abstract
In this article, the semi-analytical method was used to analyze the nonlinear dynamic stability and vibration analysis of sandwich shallow spherical shells (SSSS). The SSSS was considered as functionally graded carbon nanotube-reinforced composites (FG-CNTRC) with three new patterns of FG-CNTRC. The governing equation was obtained and discretized utilizing the Galerkin method by implementing the von Kármán-Donnell nonlinear strain-displacement relations. The nonlinear dynamic stability was analyzed by means of the fourth-order Runge-Kutta method. Then the Budiansky-Roth criterion was employed to obtain the critical load for the dynamic post-buckling. The approximate solution for the deflection was represented by suitable mode functions, which consisted of the three modes of transverse nonlinear oscillations, including one symmetrically and two asymmetrical mode shapes. The influences of various geometrical characteristics and material parameters were studied on the nonlinear dynamic stability and vibration response. The results showed that the order of layers had a significant influence on the amplitude of vibration and critical dynamic buckling load.
Abstract
In the era of smart manufacturing, precise prediction of springback—a common issue in ultra-thin sheet metal forming— and forming limits are critical for ensuring high-quality production and minimizing waste. This paper presents a novel approach that leverages the Internet of Things (IoT) and Artificial Neural Networks (ANN) to enhance springback and forming limits prediction accuracy. By integrating IoT-enabled sensors and devices, real-time data on material properties, forming conditions, and environmental factors are collected and transmitted to a central processing unit. This data serves as the input for an ANN model, which is trained with crystal plasticity simulations and experimental data to predict springback with high precision. Our proposed system not only provides continuous monitoring and adaptive learning capabilities but also facilitates real-time decision-making in manufacturing processes. Experimental results demonstrate significant improvements in prediction accuracy compared to traditional methods, highlighting the potential of IoT and ANN integration in advancing smart manufacturing. This approach promises to revolutionize quality control and operational efficiency in the industry, paving the way for more intelligent and responsive manufacturing systems.
Key Words
ANFIS model; crystal plasticity; forming limit; IoT; neural-fuzzy AI system; springback; ultrathin sheets
Address
Jing Zhao: School of Computer, Wuhan Donghu University, Wuhan 430212, Hubei, China
Lichun Wan: College of Management, Wuhan Donghu University, Wuhan 430212, Hubei, China
Mostafa Habibi: Department of Biomaterials, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai 600 077, India/ Universidad UTE, Facultad de Arquitectura y Urbanismo, Calle Rumipamba S/N y Bourgeois, Quito 170147, Ecuador/ Department of Mechanical Engineering, Faculty of Engineering, Halic University, 34060, Istanbul, Turkey/ Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam
Ameni Brahmia: Department of Chemistry, College of Science, King Khalid University, P.O. Box 9004, 61413 Abha, Saudi Arabia
Abstract
In the present research the durability and geotechnical properties of an expensive clayey soil stabilized by two different compositions of additives were investigated and compared. The first composition consisted of environmentally and ecofriendly materials: BOF steel slag ranging from 0-20% as well as rice husk ash (RHA) ranged 0-16%wt of dry soil. The other composition consisted of relatively new generation of materials including nanomaterials: nano-CaCO3 as well as nano-SiO2. Atterberg limits test, free swell percent test, swelling pressure test and unconfined compressive test were used to assess the stabilizers influences upon expansive soil geotechnical characteristics. Also, the recurrent wet-dry cycles test was exerted on experimental and non-experimental samples for estimating stabilizers effects on durability. According to the results, each of the BOF slag and RHA enhances the expansive soil properties individually, while combination of slag-RHA led to better improvement of the soil properties. Also, the composition of nano-CaCO3 and SiO2 dramatically improved the clay soil operation. The optimum values of slag+RHA were suggested as 20% slag+12% RHA to enhance percent of swelling, pressure of swelling in addition to UCS as much as 95%, 96%, and 370%, respectively. The optimum value for the second stabilizer in this study was found to be 2%nano-SiO2+2% nano-CaCO3 which led to 318% increase in UCS and 86% decrease in swelling pressure.
Key Words
expansive soil; geotechnical properties and durability; nano-materials; rice husk ash; soil stabilization; steel slag; waste materials
Address
Ali Hasan Hammadi Algabri: Department of civil engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
Seyed Alireza Zareei: Department of civil engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
Mohamed Jassam Mohamed Al Taee: College of Engineering, University of Babylon, Hilla, Iraq
Niloofar Salemi: Department of civil engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
Abstract
Graphene nanoribbons (GNRs) are considered a promising alternative to graphene for future nanoelectronic applications. However, GNRs-based device modeling is still at an early stage. This research models the electronic properties of n-doped rough-edged 13-armchair graphene nanoribbons (13-AGNRs) and quantum transport properties of n-doped rough-edged 13-armchair graphene nanoribbon field-effect transistors (13-AGNRFETs) at different doping concentrations. Step-up and edge doping are used to incorporate doping within the nanostructure. The numerical real-space nearest-neighbour tight-binding (NNTB) method constructs the Hamiltonian operator matrix, which computes electronic properties, including the sub-band structure and bandgap. Quantum transport properties are subsequently computed using the self-consistent solution of the two-dimensional Poisson and Schrödinger equations within the non-equilibrium Green's function method. The finite difference method solves the Poisson equation, while the successive over-relaxation method speeds up the convergence process. Performance metrics of the device are then computed. The results show that highly doped, rough-edged 13-AGNRs exhibit a lower bandgap. Moreover, n-doped rough-edged 13-AGNRFETs with a channel of higher doping concentration have better gate control and are less affected by leakage current because they demonstrate a higher current ratio and lower off-current. Furthermore, highly n-doped rough-edged 13-AGNRFETs have better channel control and are less affected by the short channel effect due to the lower value of subthreshold swing and drain-induced barrier lowering. The inclusion of dopants enhances the on-current by introducing more charge carriers in the highly n-doped, rough-edged channel. This research highlights the importance of optimizing doping concentrations for enhancing GNRFET-based device performance, making them viable for applications in nanoelectronics.
Address
K.L. Wong, M.W. Chuan, A. Hamzah, S. Rusli, N.E. Alias, S.M. Sultan, C.S. Lim and M.L.P. Tan: Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
Abstract
It is argued that advanced nanostructures must be integrated into ideological teaching to provide avenues for enhanced student engagement in active learning, with the ultimate goal of creating critical thinking across disciplines. In this regard, educational strategies that correspondingly address the unique structures and applications of the concept could be considered for further study, which would avail students the opportunity for interactive involvement in the educational process. This paper reflects on the potential of nano-enhanced education tools, such as nanosensors and nano-based interactive displays, in providing dynamic and responsive educational environments. It then proceeds to examine exactly how present students-using these technologies, also in the near future—can be equipped to engage with multiple ideas and perspectives to use in application. According to the findings presented, the use of advanced nanostructures in education will enhance effectiveness in methodologies of teaching and learning while preparing students for their future challenges by providing them with skills to navigate and analyze complex ideological landscapes. It is succeeded by the knowledge integration metric, which moved from an initial 61% to 87%, thereby growing by 42.62%.
Address
Binbin Zhang:College of Humanities and Law, Harbin University, Harbin 150086, Heilongjiang, China
Yong Zhang: Faculty of Economics and Management, Jiaying University, Meizhou 514015, Guangdong, China
Yun Liu: Faculty of Economics and Management, Jiaying University, Meizhou 514015, Guangdong, China/ New Era University College, Kajang 43000, Selangor, Malaysia
Amir Mohammad Zoghi: Bachelor's Student of Oudiometry, Shahid Beheshti University, Iran
T.T. Murmy: Faculty of Industrial management, Ristob company
Abstract
This paper discusses the importance of carbon nanotubes (CNTs) in enhancing performance and resistance of tennis rackets with the application of nanotechnology. This paper discusses how nanomaterials work toward making the equipment lighter, stronger, and more durable by combining CNTs with composite materials in Tennis Rackets. Distinctive properties of the CNTs, such as the very high strength-to-weight ratio and exceptional mechanical resilience, have been exploited in racket performance optimization for better power transmission, increased control on shots, and improved durability. Resistance to wear and tear is discussed in terms of the life of a CNT-enhanced tennis racket and its continued performance with time. The findings imply that the CNTs increase the security and overall performance of tennis rackets, hence promising further innovation in sports technology equipment and the various performances expected from users.
Key Words
carbon nanotubes; nanotechnology; performance; resistance; tennis racket
Address
MingYang Xie and Rui Zhang: College of Science, North China University of Technology, 100144, Beijing, China
M. Shokravi: Energy institute of higher education, Mehrab High School, Saveh, Iran
Abstract
This study investigates the stability and performance of high-resistance badminton nets through the integration of reinforced lightweight materials. By focusing on the structural and economic impacts, the research aims to enhance both the durability and practicality of badminton nets in professional and recreational settings. Using a combination of advanced material engineering techniques and economic analysis, we explore the development of nets constructed from innovative composites. These composites offer improved resistance to environmental factors, such as weather conditions, while maintaining lightweight properties for ease of installation and use. The study employs high-order shear deformation theory and high-order nonlocal theory to assess the mechanical behavior and stability of the nets. Partial differential equations derived from energy-based methodologies are solved using the Generalized Differential Quadrature Method (GDQM), providing detailed insights into the thermal buckling characteristics and overall performance. The findings demonstrate significant improvements in net stability and longevity, highlighting the potential for broader applications in both the sports equipment industry and related economic sectors. By bridging the gap between material science and practical implementation, this research contributes to the advancement of high-performance sports equipment and supports the growth of the sport economy.
Key Words
high-resistance badminton nets; reinforced lightweight materials; sport economy development; sports equipment durability; structural stability analysis; thermal buckling characteristics
Address
Qiong Wu: College of physical education, China Three Gorges University, Yichang 443002, Hubei, China/ Graduate School, Philippine Christian University, Malate 1004 Manila, Philippines
Yi Sun: School of Physical Education, DaLian University, Dalian 116622, Lioaning, China
Wanxing Yin: College of physical education, China Three Gorges University, Yichang 443002, Hubei, China
Abstract
This study introduces a novel functionally graded material model, termed the "Coated Functionally Graded Graphene-Reinforced Composite (FG GRC)" model, for investigating the free vibration response of plates, highlighting its potential to advance the understanding and application of material property variations in structural engineering. Two types of coated FG GRC plates are examined: Hardcore and Softcore, and five distribution patterns are proposed, namely FG-A, FG-B, FG-C, FG-D, and FG-E. A modified displacement field is proposed based on the higher-order shear deformation theory, effectively reducing the number of variables from five to four while accurately accounting for shear deformation effects. To solve the equations of motion, an analytical solution based on the Galerkin approach was developed for FG GRC plates resting on a viscoelastic Winkler/Pasternak foundation, applicable to various boundary conditions. A comprehensive parametric analysis elucidates the impact of multiple factors on the fundamental frequencies. These factors encompass the types and distribution patterns of the coated FG GRC plates, gradient material distribution, porosities, nonlocal length scale parameter, gradient material scale parameter, nanoplate geometry, and variations in the elastic foundation. Our theoretical research aims to overcome the inherent challenges in modeling structures, providing a robust alternative to experimental analyses of the mechanical behavior of complex structures.
Key Words
coated nanoplates; four variable higher-order shear deformation theory; nonlocal strain gradient theory; vibration response; viscoelastic foundation
Address
Ali Alnujaie and Mofareh H. Ghazwani: Department of Mechanical Engineering, College of Engineering and Computer Sciences, Jazan University, P.O Box 45124, Jazan, Saudi Arabia/ Engineering and Technology Research Center, P.O. Box 114, Jazan 82817, Saudi Arabia
Ahmed A. Daikh: Artificial Intelligence Laboratory for Mechanical and Civil Structures and Soil, University Centre of Naama, P.O. Box 66, Naama 45000, Algeria/ Laboratoire d'Etude des Structures et de Mécanique des Matériaux, Département de Génie Civil, Faculté des Sciences et de la Technologie, Université Mustapha Stambouli B.P. 305, R.P.29000 Mascara, Algérie
Amr E. Assie: Department of Mechanical Engineering, College of Engineering and Computer Sciences, Jazan University, P.O Box 45124, Jazan, Saudi Arabia/ Mechanical Design & Production Department, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt
Mohamed A Eltaher: Mechanical Engineering Department, Faculty of Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589, Saudi Arabia/ Mechanical Design & Production Department, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt
