IU Indianapolis ScholarWorks :: Browsing by Author "Moheimani, Reza"

Browsing by Author "Moheimani, Reza"

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Analysis of Composite Structures in Curing Process for Shape Deformations and Shear Stress: Basis for Advanced Optimization
(MDPI, 2021) Kumbhare, Niraj; Moheimani, Reza; Dalir, Hamid; Mechanical and Energy Engineering, School of Engineering and Technology
Identifying residual stresses and the distortions in composite structures during the curing process plays a vital role in coming up with necessary compensations in the dimensions of mold or prototypes and having precise and optimized parts for the manufacturing and assembly of composite structures. This paper presents an investigation into process-induced shape deformations in composite parts and structures, as well as a comparison of the analysis results to finalize design parameters with a minimum of deformation. A Latin hypercube sampling (LHS) method was used to generate the required random points of the input variables. These variables were then executed with the Ansys Composite Cure Simulation (ACCS) tool, which is an advanced tool used to find stress and distortion values using a three-step analysis, including Ansys Composite PrepPost, transient thermal analysis, and static structural analysis. The deformation results were further utilized to find an optimum design to manufacture a complex composite structure with the compensated dimensions. The simulation results of the ACCS tool are expected to be used by common optimization techniques to finalize a prototype design so that it can reduce common manufacturing errors like warpage, spring-in, and distortion.
Analysis of Spring-in for Composite Plates Using ANSYS Composite Cure Simulation
(American Society for Composites, 2019) Patil, Ameya; Moheimani, Reza; Shakhfeh, Talal; Dalir, Hamid; Mechanical and Energy Engineering, School of Engineering and Technology
Process induced dimensional changes in composite parts has been the topic of interest for many researchers. The residual stresses that develop in fiber-reinforced laminates during curing process while the laminate is confined to the process tool often leads to dimensional changes such as spring-in of angles and warpage of flat sections. Many experimental studies have put emphasis on this issue and various researches show different methods to predict these dimensional changes. The traditional trial-and-error approach can work for simple geometries, but composite parts with complex shapes require more sophisticated models. When composite laminates are subjected to thermal stresses, such as the heating and cooling processes during curing, they can become distorted as the difference between the in-plane and the through-thickness thermal expansion coefficient, as well as chemical shrinkage of the epoxy, causes the enclosed angle of curved sections and angle components to be reduced. Distorted components can cause problems during assembly, significantly increasing production costs and affecting performance. This paper focuses on predicting these shape deformations using software simulation of composite manufacturing and curing. Various factors such as resin shrinkage, degrees of cure, difference between coefficient of thermal expansion of mold and composite are taken into consideration. A cure kinetic model is presented which illustrates the matrix behavior during cure.
Bree's diagram of a functionally graded thick-walled cylinder under thermo-mechanical loading considering nonlinear kinematic hardening
(Elsevier, 2018-09-01) Damadam, Mohsen; Moheimani, Reza; Dalir, Hamid; Mechanical and Energy Engineering, School of Engineering and Technology
In this paper, elasto-plastic analysis of a thick-walled cylinder made of functionally graded materials (FGMs) subjected to constant internal pressure and cyclic temperature gradient loading is carried out using MATLAB. The material is assumed to be isotropic and independent of temperature with constant Poisson's ratio and the material properties vary radially based on a power law volume function relation. The Von Mises’ yield criterion and the Armstrong-Frederick nonlinear kinematic hardening model were implemented in this investigation. To obtain the incremental plastic strain, return mapping algorithm (RMA) was used. At the end, the Bree's interaction diagram is plotted in terms of non-dimensional pressure and temperature which represents an engineering index for optimum design under thermo-mechanical loading.
Engineering the electrospinning of MWCNTs/epoxy nanofiber scaffolds to enhance physical and mechanical properties of CFRPs
(Elsevier, 2021-09) Wable, Vidya; Biswas, Pias Kumar; Moheimani, Reza; Aliahmad, Nojan; Omole, Peter; Siegel, Amanda P.; Agarwal, Mangilal; Dalir, Hamid; Mechanical Engineering, School of Engineering and Technology
A cost-effective approach to improve the physical and mechanical properties of carbon fiber reinforced polymer (CFRP) prepreg composites, where electrospun multiwalled carbon nanotubes (MWCNTs)/epoxy nanofibers were synthesized and incorporated in between the layers of conventional CFRP prepreg composite has been presented. MWCNT-aligned epoxy nanofibers were successfully produced by an optimized electrospinning process. Nanofibers were deposited directly onto prepreg layers to achieve improved adhesion and interfacial bonding, leading to added strength and improvements in other mechanical properties. Thus, interlaminar shear strength (ILSS) and fatigue performance at high-stress regimes increased by 29% and 27%, respectively. Barely visible impact damage (BVID) energy increased significantly by up to 45%. The thermal and electrical conductivities were also enhanced significantly due to the presence of the highly conductive MWCNT networks between the CFRP layers. The presented method was capable of uniformly depositing high contents of MWCNTs at interlaminar ply interface of prepregs to strengthen/enhance CFRP properties, which has not been previously shown to be possible due to high resin viscosity caused by randomly oriented MWCNTs in epoxy system.
Failure study of fiber/epoxy composite laminate interface using cohesive multiscale model:
(SAGE, 2020-03-18) Moheimani, Reza; Sarayloo, Reza; Dalir, Hamid; Mechanical and Energy Engineering, School of Engineering and Technology
In this study, finite element modeling is performed to investigate the compressive failure of the composite sandwich structures with layered composite shells. An embedded debond area between the layered composite shell and the foam core is assumed as a defect. The composite shells are several plies of equal thickness Kevlar, carbon fiber composite, and E-glass composite with epoxy resin. Three different lay-ups, namely, (0°/90°/0°/90°/0°/90°), (45°/−45°/0°/90°/60°/−30°), and (60°/−30°/90°/0°/30°/90°) are considered for symmetric and asymmetric sequences. The work focuses on the importance of cohesive zone model versus the previously conducted numerical simulation and experimental results for buckling of sandwich composite structures. This enables one to account for delamination growth between shells and core and improve the correlation results with those of experiments. It has been shown that not only the cohesive model is capable of demonstrating delamination propagation, but it also correlates very well with the experimental data. By compiling user-defined cohesive mesoscale model in Abaqus simulation, the local and global buckling of the face-sheets can be precisely detected and response of sandwich structure becomes mesh independent, while mesh size is reduced.
An Integrated Nanocomposite Proximity Sensor: Machine Learning-Based Optimization, Simulation, and Experiment
(MDPI, 2022-04-08) Moheimani, Reza; Gonzalez, Marcial; Dalir, Hamid; Mechanical and Energy Engineering, School of Engineering and Technology
This paper utilizes multi-objective optimization for efficient fabrication of a novel Carbon Nanotube (CNT) based nanocomposite proximity sensor. A previously developed model is utilized to generate a large data set required for optimization which included dimensions of the film sensor, applied excitation frequency, medium permittivity, and resistivity of sensor dielectric, to maximize sensor sensitivity and minimize the cost of the material used. To decrease the runtime of the original model, an artificial neural network (ANN) is implemented by generating a one-thousand samples data set to create and train a black-box model. This model is used as the fitness function of a genetic algorithm (GA) model for dual-objective optimization. We also represented the 2D Pareto Frontier of optimum solutions and scatters of distribution. A parametric study is also performed to discern the effects of the various device parameters. The results provide a wide range of geometrical data leading to the maximum sensitivity at the minimum cost of conductive nanoparticles. The innovative contribution of this research is the combination of GA and ANN, which results in a fast and accurate optimization scheme.
Mathematical Model and Experimental Design of Nanocomposite Proximity Sensors
(IEEE, 2020-08) Moheimani, Reza; Pasharavesh, Abdolreza; Agarwal, Mangilal; Dalir, Hamid; Engineering Technology, School of Engineering and Technology
A mathematical model of fringe capacitance for a nano-based proximity sensor, which takes the presence of different resistivities into account, is developed. An analytical solution obtained for a rectangular-shape sensor with applying of Gauss, Conversation of Charge and Ohm laws into Laplace's equation ∇2V (x, y, z, t) = 0 gives the electric potential distribution by which the fringe capacitance in a 2D domain area can be calculated. The calculated capacitance evidently decreases drastically due to the fringe phenomena while object moves toward the polymeric sensor. The model also asserts that the change of capacitance is under a noticeable influence of sensor resistivity, particularly in the range of 103-105Ω.m, the initial capacitance varies from 0.045pF to 0.024 pF. The fabricated flexible nanocomposite sensors, Thermoplastic Polyurethane (TPU) reinforced by 1wt.% Carbon Nanotubes (CNTs) having resistivity 105Ω.m, are capable of detecting presence of an external object in a wide range of distance and indicating remarkable correlation with the mathematical solution. Our proximity sensor fabrication is straightforward and relatively simple. An unprecedented detection range of measurement reveals promising ability of this proximity sensor in applications of motion analysis and healthcare systems.
Nonlinear energy harvesting from vibratory disc-shaped piezoelectric laminates
(Elsevier, 2020-04) Pasharavesh, Abdolreza; Moheimani, Reza; Dalir, Hamid; Mechanical and Energy Engineering, School of Engineering and Technology
Implementing resonators with geometrical nonlinearities in vibrational energy harvesting systems leads to considerable enhancement of their operational bandwidths. This advantage of nonlinear devices in comparison to their linear counterparts is much more obvious especially at small-scale where transition to nonlinear regime of vibration occurs at moderately small amplitudes of the base excitation. In this paper the nonlinear behavior of a disc-shaped piezoelectric laminated harvester considering midplane-stretching effect is investigated. Extended Hamilton’s principle is exploited to extract electromechanically coupled governing partial differential equations of the system. The equations are firstly order-reduced and then analytically solved implementing perturbation method of multiple scales. A nonlinear finite element method (FEM) simulation of the system is performed additionally for the purpose of verification which shows agreement with the analytical solution to a large extent. The frequency response of the output power at primary resonance of the harvester is calculated to investigate the effect of nonlinearity on the system performance. Effect of various parameters including mechanical quality factor, external load impedance and base excitation amplitude on the behavior of the system are studied. Findings indicate that in the nonlinear regime both output power and operational bandwidth of the harvester will be enhanced by increasing the mechanical quality factor which can be considered as a significant advantage in comparison to linear harvesters in which these two factors vary in opposite ways as quality factor is changed.
Performance Analysis of an Electromagnetically Coupled Piezoelectric Energy Scavenger
(MDPI, 2020-01) Pasharavesh, Abdolreza; Moheimani, Reza; Dalir, Hamid; Mechanical and Energy Engineering, School of Engineering and Technology
The deliberate introduction of nonlinearities is widely used as an effective technique for the bandwidth broadening of conventional linear energy harvesting devices. This approach not only results in a more uniform behavior of the output power within a wider frequency band through bending the resonance response, but also contributes to energy harvesting from low-frequency excitations by activation of superharmonic resonances. This article investigates the nonlinear dynamics of a monostable piezoelectric harvester under a self-powered electromagnetic actuation. To this end, the governing nonlinear partial differential equations of the proposed harvester are order-reduced and solved by means of the perturbation method of multiple scales. The results indicate that, according to the excitation amplitude and load resistance, different responses can be distinguished at the primary resonance. The system behavior may involve the traditional bending of response curves, Hopf bifurcations, and instability regions. Furthermore, an order-two superharmonic resonance is observed, which is activated at lower excitations in comparison to order-three conventional resonances of the Duffing-type resonator. This secondary resonance makes it possible to extract considerable amounts of power at fractions of natural frequency, which is very beneficial in micro-electro-mechanical systems (MEMS)-based harvesters with generally high resonance frequencies. The extracted power in both primary and superharmonic resonances are analytically calculated, then verified by a numerical solution where a good agreement is observed between the results.
Recent Advances on Capacitive Proximity Sensors: From Design and Materials to Creative Applications
(MDPI, 2022) Moheimani, Reza; Hosseini, Paniz; Mohammadi, Saeed; Dalir, Hamid; Mechanical and Energy Engineering, Purdue School of Engineering and Technology
Capacitive proximity sensors (CPSs) have recently been a focus of increased attention because of their widespread applications, simplicity of design, low cost, and low power consumption. This mini review article provides a comprehensive overview of various applications of CPSs, as well as current advancements in CPS construction approaches. We begin by outlining the major technologies utilized in proximity sensing, highlighting their characteristics and applications, and discussing their advantages and disadvantages, with a heavy emphasis on capacitive sensors. Evaluating various nanocomposites for proximity sensing and corresponding detecting approaches ranging from physical to chemical detection are emphasized. The matrix and active ingredients used in such sensors, as well as the measured ranges, will also be discussed. A good understanding of CPSs is not only essential for resolving issues, but is also one of the primary forces propelling CPS technology ahead. We aim to examine the impediments and possible solutions to the development of CPSs. Furthermore, we illustrate how nanocomposite fusion may be used to improve the detection range and accuracy of a CPS while also broadening the application scenarios. Finally, the impact of conductance on sensor performance and other variables that impact the sensitivity distribution of CPSs are presented.

Browsing by Author "Moheimani, Reza"

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