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Extending a higher-order foldability constitutive model for dynamic response analysis of 3D-reinforced shell of deformable
(Springer Science and Business Media LLC, 2025-01-20)
Xizhu Li
;
Ling Luo
;
Mostafa Habibi
;
Luyao Wang
This analytical paper investigates application of a novel higher-order shear deformable mathematical model for investigating vibrational analysis of a doubly curved shell in which the kinematic relations are extended using the variable-thickness transverse deflection. The Hamiltonian method is extended to derive the governing motions equations in the curvilinear coordinate system. The constitutive relations are extended using the experimental and statistical relations in the literature for a copper matrix including various amount of three-dimensional graphene nanofillers named as graphene origami using hydrogenation process. The analytical results are presented using the mathematical model in order to trace the impact of graphene origami characteristics and geometric parameters of the double-curved shell. The temperature-dependency relations for material properties as well as folding and content are employed for investigating the impact of affecting parameters. The results are presented with and without thickness stretching effect to arrive at a more confidence results.
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Biodiesel synthesis from waste coconut scum oil utilizing SnFe2O4/cigarette butt-derived biochar as a magnetic nanocatalyst: Optimization, kinetic and thermodynamic study
(Elsevier BV, 2024-10)
Yi Man
;
Mostafa Habibi
;
Basir Maleki
This study aims to develop a novel and efficient magnetic nanocatalyst for producing biodiesel from waste coconut scum oil (WCSO). In this regard, a retrievable and robust nanocatalyst, SnFe2O4/biochar derived from cigarette butts, was synthesized and applied in the transesterification of WCSO under ultrasonication. The aforementioned nanocatalyst was synthesized by sol-gel technique. Various analyses were conducted to characterize the prepared nanocatalyst. These analyses confirmed the successful decoration of biochar on SnFe2O4. The Surface area and pore diameter were 128.47 m2/g and 15.62 nm, respectively. Central composite design (CCD) was applied to optimize the parameters influencing biodiesel synthesis. Moreover, the highest biodiesel yield employing SnFe2O4/cigarette butt-derived biochar nanocatalysts was attained at 98.67 % under optimal conditions, which include a methanol/WCSO ratio of 11.81:1 mol/mol, ultrasonic time of 34.25 min, temperature of 64.05 °C, and a catalyst amount of 2.73 wt%. Besides, SnFe2O4/cigarette butt-derived biochar demonstrated a notable biodiesel yield (90.48 %) even after seven reuse steps, highlighting its exceptional reusability. The thermodynamic and kinetic analyses of transesterification indicate that the synthesis of biodiesel is an endothermic reaction. The SnFe2O4/cigarette butt-derived biochar nanocatalyst stands out as a highly promising candidate for future research due to biodiesel performance, quick reaction time, and remarkable catalyst reusability.
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Bending-based solution methodology using eigenvalue-eigenvector approach for analysis of foldable reinforced Golf Clubs cylindrical shell
(Informa UK Limited, 2024-07-21)
Jingxian Huang
;
Zhidao Pan
;
Sheng Yang
;
Mostafa Habibi
;
Maryam Safa
This paper is organized to present eigenvalue-eigenvector based solution method for elastic bending analysis of foldable Golf Clubs cylindrical shell reinforced with graphene origami. The axisymmetric kinematic and constitutive relations are extended using the models with shear deformability and three-dimensional relations. The effective material properties are inserted into integration constants and constitutive relations in terms of angle and content of folded structure as well as thermal load. The virtual work principle is extended in order to derive governing equations and the eigenvalue-eigenvector method is applied for analytical solution. The results are presented along the longitudinal and radial coordinates with changes of angle and content of folded structure as well as thermal load. The results of this analysis may be used for optimized design and manufacturing of the golf clubs and other sport equipment.
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Bending responses of graphene nanoplatelets reinforced sandwich cylindrical micro panel with piezoelectric layers
(Informa UK Limited, 2024-08-04)
Qian Zhang
;
Mingchao Xie
;
Dianyi Zhou
;
Mostafa Habibi
;
KHORAMI, MAJID
There are some inevitable challenges during the manufacturing of reinforced composite structures. Agglomeration of reinforcement and wavy reinforcement are in this category. These phenomena possess remarkable effects on the mechanical behavior of reinforced composite structures. In the current research, the effect of agglomeration and waviness of reinforcements on torsional dynamic characteristics of multi-walled carbon nanotubes (MWCNTs) reinforced composite rods subjected to two various boundary conditions have been evaluated. Three dissimilar cross-section shapes have been considered to understand the effect of cross-section shapes on torsional behavior of MWCNTs-reinforced composite rods. A new form of Halpin-Tsai homogenization model has been exerted to estimate the material properties of composite structures. Additionally, Timoshenko-Gere theory in conjunction with the Hamilton's principle has been employed to derive the partial differential governing equation of MWCNTs-reinforced composite rods. Afterward, the obtained equation was solved using an analytical approach. The precision of the methodology utilized has been evaluated against the results of previous studies documented in the literature. Ultimately, the effects of various significant parameters on the changes in natural torsional frequency have been analyzed and presented in a series of tables and figures. Based on the obtained results, the rectangular rod has the highest torsional frequency and also the effect of MWCNTs’ volume fraction depends on the consideration of waviness and agglomeration factors. At a greater volume fraction of MWCNTs, the agglomeration factor is more effective than the waviness factor and vice versa.
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AI-assisted prediction of St14 steel sheets formability: Neural-fuzzy systems and crystal plasticity assessments
(Elsevier BV, 2024-07)
Zhao Zisong
;
Mostafa Habibi
We've introduced a new technique leveraging artificial intelligence to determine in-plane forming limit strains in St14 sheet metals. A neural-fuzzy AI system was devised to predict safe points on forming limit diagrams, considering aspects like crystal texture, metal sheet thickness, and spherical punch diameter. Neural-fuzzy systems could be utilized in prediction of forming limit curves using linguistic data description. To obtain the data required for training the AI network, in-depth tests, including XRD, metallography, tensile testing, and Nakazima's hemisphere evaluations, were carried out to detail the metallurgical and mechanical properties of St14 sheet metal. Data on texture, the tensile curves, and grain morphology were then incorporated in crystal plasticity models to find hardening constants for St14's single crystals. Using these determined values, Nakazima's tests were replicated through multi-crystal aggregate configurations. We then undertook a comprehensive parameter investigation via 324 crystal plasticity simulations to shed light on the effects of texture, sheet depth, and punch dimensions on St14's formability. This rich dataset paved the way for training an adaptive neural fuzzy inference system (ANFIS), leading to substantial reductions in time and computational needs. The results validate that the ANFIS model offers accurate and reliable predictions, highlighting its viability for wider use in determining forming limit diagrams.
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Electroelastic wave dispersion in the rotary piezoelectric NEMS sensors/actuators via nonlocal strain gradient theory
(Elsevier BV, 2024-07)
Yuan Guo
;
Allam Maalla
;
Mostafa Habibi
;
Zohre moradi
This article introduces a computational means for investigating the electroelastic nonlinear wave dispersion traits of the nano-dimension sandwich pipe, which is composed of a core formed of a bi-directional functionally graded (Bi-FG) material, together with a piezoelectric sensor/actuator. A combination of Hamilton's principle, first-order shear deformation, along with Von-Karman nonlinearity, is used for modeling and obtaining the nonlinear governing equations of the nano-sized sandwich pipe connected to a piezoelectric part. The nonlinear governing equations to obtain the nonlinear phase velocity of the current system are determined using a combination of analytical and multiple scales approaches. Due to some computational cost for choosing the precise values of both the nonlocality factor and length scale of the nanopipe in the laboratory, for the first time in this research, with the aid of COMSOL multi-physics finite element simulation, the results are verified, and new outcomes for obtaining the exact functions for nonlocal and length scale factors is presented. In addition, an artificial neural network (ANN) is utilized in this study for the prediction of the results. The mathematical and finite element results were used to train the ANN. A newly presented optimization algorithm is exploited for the first time for optimizing the ANN parameters concluding higher accuracy of the ANN predictions. Consequently, to explore the influences of the location of the piezoelectric patch, nonlocality and length scale factors, and applied voltage parameter on the phase velocity characteristics of the nano-dimension sandwich pipe made of a Bi-FG core and electrically patch, an effort is performed. As an applicable result that can be useful in the related nano-industries, the current work presents exact nonlocal and length scale functions for different conditions.
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An inspection of the metal-foam beam considering torsional dynamic responses
(Elsevier BV, 2024-11)
Jiaman Li
;
Zhixin Wu
;
Mostafa Habibi
;
Ibrahim Albaijan
Metal foam is a multifunctional material with a lower specific weight, high stiffness and compressive strength, and high energy absorption. These remarkable properties make metal foams a promising candidate for conventional materials in different industrial fields. Despite numerous researches on mechanical behavior either static or dynamic of structures made of metal foams, torsional vibration analysis of metal foam structures is still uninvestigated. In this investigation, the influence of various imperfection distribution patterns on the torsional dynamic response of metal foam beams is examined within the framework of Timoshenko-Gere's theory. Two common materials i.e. SUS304 and Aluminum foams are considered the constructive materials of structure. Moreover, three imperfection distribution patterns are taken into account. The virtual work's principle has been employed to derive the torsional governing equation of metal foam beams. Then, the derived governing equation has been solved via an analytical method. The accuracy of the employed methodology has been compared with the findings of former research in the literature. Finally, the influences of different notable parameters on the variation of natural torsional frequency have been examined and demonstrated in a group of tables and diagrams.

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