Effects Of Material Properties Research Articles

Spatio-Selective Reconfiguration of Mechanical Metamaterials Through the Use of Dynamic Covalent Chemistries.

Mechanical metamaterials achieve unprecedented mechanical properties through their periodically interconnected unit cell structure. However, their geometrical design and resulting mechanical properties are typically fixed during fabrication. Despite efforts to implement covalent adaptable networks (CANs) into metamaterials for permanent shape reconfigurability, emphasis is given to global rather than local shape reconfiguration. Furthermore, the change of effective material properties like Poisson's ratio remains to be explored. In this work, a non-isocyanate polyurethane elastomeric CAN, which can be thermally reconfigured,is introduced into a metamaterial architecture. Structural reconfiguration allows for the local and global reprogramming of the Poisson's ratio with change of unit cell angle from 60° to 90° for the auxeticand 120° to 90° for the honeycomb metamaterial. The respective Poisson's ratio changes from -1.4 up to -0.4 for the auxetic and from +0.7 to +0.2 for the honeycomb metamaterial. Carbon nanotubes are deposited on the metamaterials to enable global and spatial electrothermal heating for on-demand reshaping with a heterogeneous Poisson's ratio ranging from -2 to ≈0 for a single auxetic or +0.6 to ≈0 for a single honeycomb metamaterial. Finite element simulations reveal how permanent geometrical reconfiguration results from locally and globally relaxed heated patterns.

Fin angles optimization of water-cooled plate-fin heat sink based on anisotropic Darcy–Forchheimer theory

Flat heat sinks are devices for efficient heat dissipation and are important components in manufacturing. For example, in precision glass molding, it is utilized as a cooling plate contributing to improve the quality of the product by reducing residual stress and shape deviation, during the gradual cooling phase. In this study, we attempted to achieve precise temperature design of the cooling plate using variable lattice optimization. Fins allow for controlling the flow direction and achieving efficient heat transfer. Therefore, elliptical cylindrical fins were adopted as lattice unit cells, increasing the design freedom of the flow field. To account for the asymmetric flow field within the unit cell, we introduced an asymmetric tensor for the coefficients of the effective physical properties in the Darcy–Forchheimer equation. The proposed method's effectiveness and validity are discussed through numerical calculations with effective material properties, reproduced detailed shapes, and experimental verification. The optimization aiming to minimize the average temperature yielded a numerical simulation temperature decrease of 24.6 % and an experimental temperature decrease of 14.1 % compared to the benchmark model.

Experimental characterization of the effective acoustic properties of anisotropic porous materials via free-field measurements

Porous media are commonly described as effective isotropic fluid materials, such that their acoustic properties can be adequately determined from their bulk modulus and dynamic density. Most acoustic absorbents, however, possess a marked anisotropy, which influences their acoustical behavior and the parameters necessary to deduce it. Specifically, the influence of anisotropy translates into a full symmetric density tensor (in place of a scalar). This study presents a method for retrieving the bulk modulus and all six components of the density tensor of a layer of porous material from reflection coefficients measured in free field with an array of microphones. The procedure consists in expressing the sound field measured in the vicinity of the layer as a superposition of plane waves, from which the surface impedance and the reflection coefficient are reconstructed. The reflection properties, as well as the pressure at the rigid backing interface, are estimated for various source positions (i.e., various angles of incidence) and an inverse problem is formulated to infer the effective fluid parameters. The validity of the method is examined experimentally on a manufactured porous material, and the resulting fluid parameters compared with experimental results obtained from reflection and transmission coefficients measured in an impedance tube.

Static analysis of foldable pressurized and thermally loaded cylindrical shell as an expander in sport equipment reinforced by G-Ori nanofillers

The present work investigates stress, strain and deformation analyses of a shear deformable cylindrical shell manufactures by a Copper (Cu) core reinforced with graphene origami auxetic metamaterial subjected to mechanical and thermal loads. The cylindrical models can be used in sport equipment especially in expander component. The effective material properties of the graphene origami auxetic reinforced Cu matrix are developed using micromechanical models cooperate both material properties of graphene and Cu in terms of local temperature, volume fraction and folding degree. The principle of virtual work is used to derive governing equations with accounting thermal loading.

Stability and vibration control of electrostatically excited functionally graded microresonator using nonlinear observer based sliding mode controller

The dynamic stability analysis of microsystems is an important aspect in understanding the critical operating regions under different excitations. Present study proposes an observer-based adaptive back-stepping sliding mode controller (ABSMC) model to control and stabilize an electrostatically excited functionally graded microresonator. The dynamic model of a microsystem subjected to random disturbances is derived using modified couple stress theory and Euler–Bernoulli’s beam model. The effective material properties are obtained from Mori-Tanaka scheme and the equations of motion are derived using Hamilton principle and solved by Galerkin’s method. A trained neural network estimator predicts the disturbances and the adaptive back-stepping sliding mode controller is designed for improving the system stability. The results of the proposed controller are compared with conventional sliding mode control (SMC) and proportional-derivative (PD) control solutions and it is found that ABSMC reduces settling time and input control force by 52.42% and 88.40%, respectively, with minimal chattering. The proposed control methodology effectively extends the travelling range of FG microsystems within and beyond the pull-in voltage.

Computer Simulation of Deformation characteristics of Hybrid Orthotropic Composite Sandwich Beams Under Bending and Axial Loading

This study focuses on the deformation characteristics of hybrid orthotropic composite sandwich beams under axial and bending loading. The homogeneous cores of the hybrid orthotropic sandwich beams affect different parameters on structures. We followed by analytically determining effective material properties to study response of the hybrid sandwich beam under axial and bending loading. Ensuing, we programmed all steps and procedures of solution algorithm into commercially available MATLABTM 2020 code to simulate practical scenarios. Subsequently, we collected and processed data in tabular and graphical forms to facilitate analyses. We compared simulation generated results to the data results available in the literature and found to be within the acceptable range of (±6%) deviations. We observed that the hybrid structure beams had undergone less deformation that confirmed that the hybrid structure beams have comprehensive mechanical advantages as well as has high strength and specific energy absorption capabilities. Based on comparison of the results, the hybrid beams are more damage resistant and tolerant than beams made of the other type of materials. Since hybrid sandwich beams are relatively light, economical, and perform better under axial and bending deformations. Therefore, this study could also be extended to investigate performance of the orthotropic sandwich beam structures under multiple loading directions as well as proposes that the usage of the hybrid sandwich beam components will be useful in global structures.

Multiscale modelling and characterisation of fused filament fabricated neat and graphene nanoplatelet reinforced G-polymers

AbstractIn this study, the fused filament fabrication of novel biodegradable G-polymer is investigated, including also filaments reinforced by graphene nanoplatelets. A combined framework of computational multiscale modelling and experimental studies is applied to characterise and model the mechanical behaviour of composite and nanocomposite materials, fabricated using a 3D-printer by depositing G-polymer filaments in +45$$^\circ$$ ∘ and $$-45^\circ$$ - 45 ∘ angles. The investigation is performed on both hot-extruded single filaments and 3D-printed specimens. Experimental results of hot-extruded single filaments are utilized on the microscale to extract the macroscale constitutive models. At the microscale level, representative volume elements with different percentages of penetration are analyzed to compute the effective orthotropic elastic material properties. A comprehensive comparison study is conducted using different micromechanical models, multiscale simulation outputs, and the mechanical properties resulting from experiments. The accuracy of the results obtained from the homogenization technique is validated against realistic finite element microstructural models and experimental measurements. The results demonstrate that computational homogenization, when coupled with accurate property characterisation, serves as a reliable tool for predicting the elastic response of 3D-printed parts. Furthermore, the proposed framework reduces the need for extensive experimental replication and lowers manufacturing costs.

Material Homogenization of Human Femur Bone Material Using a New Weighted Approach

Abstract The design of efficient and safe biocompatible artificial implants for bone replacement and reconstructions requires a thorough understanding of natural bone material. A new homogenization approach is therefore used to predict effective material properties of the human femur bone. The bone structure is idealized as a functionally graded composite made of different quantities of a collagen protein matrix reinforced by hydroxyapatite mineral acting as the filler. Two distinct composite models were investigated, one where the mineral reinforcements were assumed to be randomly dispersed inclusions in a matrix of collagen, and a second model wherein the minerals were assumed to be unidirectional fibers. Predicted results for longitudinal and transverse elastic modulus from the models compare very well with range of values from published experimental data. It is also compared to those predicted using classical homogenization models. These material properties are then used to obtain the structural response of a bone plate section under transverse load.

Effective Electromagnetic Properties of Composite Material Computed From Neural Network Approach

ABSTRACTThanks to their lightweight, composite materials have become widely used in the automotive and aerospace industries. The design of components made from these materials is carried out by numerical modeling which can sometimes be tedious because of the need to take into account the internal structure of these materials. Obtaining the effective properties of an equivalent homogeneous material to replace the composite in our numerical models makes modeling easier. Classical homogenization approaches are not always suitable to obtain these effective properties. This article deals with an inverse problem that consists in computing the electromagnetic properties from the knowledge of the magnetic shielding effectiveness values. For different composite samples, an artificial neural network method is used to predict the effective conductivities from the magnetic shielding effectiveness measurements. The magnetic shielding effectiveness values computed from the predicted conductivities are close to those obtained from the measurements.

Engineered moiré photonic and phononic superlattices.

Recent discoveries of Mott insulating and unconventional superconducting states in twisted bilayer graphene with moiré superlattices have not only reshaped the landscape of 'twistronics' but also sparked the rapidly growing fields of moiré photonic and phononic structures. These innovative moiré structures have opened new routes of exploration for classical wave physics, leading to intriguing phenomena and robust control of electromagnetic and mechanical waves. Drawing inspiration from the success of twisted bilayer graphene, this Perspective describes an overarching framework of the emerging moiré photonic and phononic structures that promise novel classical wave devices. We begin with the fundamentals of moiré superlattices, before highlighting recent studies that exploit twist angle and interlayer coupling as new ingredients with which to engineer and tailor the band structures and effective material properties of photonic and phononic structures. Finally, we discuss the future directions and prospects of this emerging area in materials science and wave physics.

Concurrent topology optimization of sandwich structures with multi-configuration and variable-diameter lattice infill

The superior stiffness-to-weight and strength-to-weight mechanical advantages of sandwich structures can be fully exploited through concurrent design of entire topology, infill configuration and density, where the high-performance yet complicated structure can be fabricated through additive manufacturing. However, the emerging design challenges are concurrent design updating related to sandwich topology, infill configuration and density, which is a design problem with continuous and discrete variables mathematically. In this paper, a concurrent topology optimization is proposed for sandwich structures with multi-configuration and variable-diameter lattice infill. Three design variable fields are employed to describe the fundamental topology considering sandwich structural topology, infill configuration and density simultaneously. Corresponding material interpolation model is developed by combining DSP-based shell-infill description and multi-response latent-variable surrogate model based effective material property calculation. Two-stage design model is formulated as a rough design model considering all design variables followed by a refined design model with only infill density variables, which is developed to strictly satisfy the material allowance constraint due to the mapping between discrete infill configuration variables and continuous latent configuration variables. Corresponding sensitivities of compliance and constraint with respect to the structural topology, infill configuration and density variables are derived, and the method of moving asymptotes (MMA) is employed to solve the design model efficiently. Several numerical examples are presented to systematically demonstrate the effectiveness of the proposed approach.

Semi-analytical framework for modelling of surface heating and its impact on nonlinear stability of nanotube reinforced doubly curved porous fiber composite panels

In elevated temperatures, the stiffness of the panel deteriorates and can lead to loss of stability of structures. Hence, the stability analysis of thin-walled structures is a critical investigation in the thermal environment. Finding such criticality, the present semi-analytical study investigated the nonlinear stability behaviour of porous doubly curved thin-walled panels subject to surface heating like dome heating and localised heating. To improve the stiffness of the panel, the matrix is reinforced with carbon nanotubes (CNTs). Improper mixing of such nanoparticles can lead to agglomeration or bundling effect, which may reduce the structure's stiffness. Still, its investigation in surface heating can be an essential aspect that is found to be untouched by researchers for porous shell panels. The effective material properties of the three-phase composite panel are determined using the Eshelby-Mori-Tanaka (E-M-T) approach and the Chamis homogenisation technique. Using the variational principle, governing equations are derived and further simplified to non-linear algebraic equations using the Galerkin technique. Gibson and Ashby foam model is used to model cell structure. It is observed that a complete agglomerated state results in higher post-buckling strength, a continuous deformation path due to biaxial compression and curved geometry, and porosity of cellular structure distribution and cell walls are the important parameters to study the stability of panel in a thermal environment are the major conclusions drawn from the current study. Current investigation can be an important contribution towards modelling aircraft structure in supersonic airflow and furnace walls of thermal power plants subjected to localised heating.

Dynamic homogenization of inhomogeneous elastic media based on energy equivalence

This paper presents a new method of dynamic homogenization of periodic elastic media under harmonic antiplane deformation based on energy equivalence. The dynamic homogenization is based on two main steps, (1) determining the dispersion relation and the detailed local response in a representative volume element (RVE) by analyzing the propagation of Bloch waves and (2) using energy equivalence between the periodic and effective media to determine the effective properties. The method is first applied to a one-dimensional periodic medium, from which the analytical solutions of the effective material properties are obtained. The results are compared with that from the original periodic medium and an excellent agreement is observed. The dynamic homogenization method is then applied to general two-dimensional periodic media to determine the effective properties and to predict wave fields under typical loading conditions. Illustrative examples are presented and compared with the results from the multiple scattering model. The method has also been applied to multiscale modeling of complicated inhomogeneous media containing multiple groups of periodic inhomogeneities. By treating each group as a homogeneous material with effective properties determined by the current homogenization method, the wave field is obtained using the boundary element method. The resulting wave fields from the current method show an excellent agreement with that from the multiple scattering model with matching local response details.

Free vibration analysis of functionally graded composite plates reinforced with linearly and nonlinearly distributed carbon nanotubes in hygrothermal environments

This article presents a novel investigation of the free vibration behavior of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) plates under hygrothermal environments. It explores both uniform and non-uniform (functionally graded) distributions of CNTs across the plate thickness for the first time. The effective material properties of the CNTRC, considering temperature and moisture dependence, are determined using the extended rule of mixture. First-order shear deformation theory (FSDT) is employed to derive the governing equations incorporating hygro-elastic and thermo-elastic relations. These equations are solved using the finite element method. A validation study verifies the accuracy of the employed approaches. Subsequently, a comprehensive parametric study investigates the influence of plate geometry (length-to-width and width-to-thickness ratios), CNTs volume fraction, boundary conditions, linear and non-linear CNTs distributions, and hygrothermal environments on the free vibration behavior of polymeric nanocomposite plates reinforced with CNTs fillers is conducted. The results reveal that the increase in temperature and moisture leads to a decrease in the effective stiffness of the FG-CNTRC plates.

Nonlinear vibrations of variable speed rotating graphene platelets reinforced blades subjected to combined parametric and forced excitation

It is generally acknowledged that the disturbance of rotating speed will cause parametric resonance for blades, and the presence of rotor displacement also can make the blade vibrate transversely. However, the coupled resonance mechanism of blades under the combined action of rotating speed disturbance and rotor displacement is not yet clear. To answer this question, this article investigates the nonlinear coupled resonance behavior of rotating blades in two cases: typical tuned (the frequency ratio of parametric and forced excitations equals 2:1) and frequency ratio detuned. A nonlinear vibration equation for rotating blades is established based on Euler beam theory in conjunction with geometric nonlinearity. The mixing rule and modified Halpin-Tsai model are used to calculate the effective properties of GPLRMF materials. Subsequently, using the method of varying amplitudes (MVA), an approximate analytical solution of the coupled resonance response is derived, the Jacobian matrix is used to determine the stability of non-trivial solutions, and the accuracy of the analytical results is verified with the aid of numerical solutions. Finally, the steady-state response of typical tuned and detuned coupled resonance is analyzed, and the influence mechanism of factors such as excitation amplitude, excitation phase angle and other parameters on coupled resonance is studied in detail. The results indicate that the supercritical coupled resonance curve exhibits double resonance peaks and jumps. Meanwhile, the steady-state response of coupled resonance highly depends on the excitation phase angle.

Uncertainty quantification for locally resonant coated plates and shells

The effect of uncertainty in design parameters on the acoustic performance of coated plates and coated shells for maritime applications is presented. The locally resonant coatings are designed using a viscoelastic material with an impedance similar to water and embedded with layers of inclusions. Both voids and hard inclusions, which respectively exhibit monopole and dipole resonance scattering, are considered. Effective medium approximation theory is employed to characterise the layers of inclusions as homogenised layers with effective material and geometric properties. The coating is then modelled as a multilayered equivalent fluid composed of alternating layers of the homogeneous viscoelastic material and the homogenised layers of inclusions. The coating is bonded to a rigid backing plate and the acoustic response is calculated using the transfer matrix method. The coating is also externally applied to an elastic cylindrical shell. The acoustic response is calculated by expressing the shell displacements and acoustic pressures in the coating and exterior domain in terms of Fourier series expansions, and applying continuity equations at each interface between the shell surface, coating layers and the surrounding water. Efficient stochastic models based on the non-intrusive polynomial chaos expansion (PCE) method are developed by transforming the analytical models for the coated plates and shells into computationally efficient surrogate models using point collocation. Uncertainty in dominant design parameters associated with the geometry of the inclusions and material properties of the coating is examined. The influence of the design parameters for inclusions tuned to different resonance frequencies and for multiple layers of inclusions is also reported. Strong acoustic performance of coating designs occurs in a broad frequency range around local resonance of the inclusions. For all coating models, uncertainty in parameters which predominantly influence the local resonance of the inclusions were observed to yield the greatest variation in the acoustic responses of the coated plates and shells.

Thermal modeling of porous medium integrated in PCM and its application in passive thermal management of electric vehicle battery pack

The integration of a composite of porous medium with phase change material (PCM) offers significant advantages in thermal management systems, enhancing heat transfer efficiency and addressing various thermal regulation challenges. This approach utilizes the PCM's latent heat absorption and the enhanced thermal conductivity provided by the porous medium, resulting in optimized system performance. Its applicability spans across electronics cooling and building insulation systems. However, predicting the thermal behavior of this composite material is challenging, necessitating computational tools to anticipate its response under different conditions and evaluate its influence on cooling strategies. The objective of this study is to create a computational tool specifically tailored to evaluate constitutive parameters of this composite material, thereby providing a comprehensive description of its thermal behavior. To achieve this goal, the multiscale homogenization principle is employed to assess the composite's effective thermophysical material properties using the representative volume element approach. The repeating unit cell of the aluminum lattice is incorporated into the PCM to define a representative volume element. The finite element method (FEM) is utilized to solve the three-dimensional homogenization problem, yielding an orthotropic effective thermal conductivity due to the inherent symmetry of the repeating material cell. Moreover, the study leverages the apparent heat capacity method to effectively manage the phase transitions within the PCM domain, utilizing smooth and temperature-dependent functions to accurately describe the thermophysical properties of the PCM. Integrating the composite into battery pack thermal management, this study thoroughly examines thermal dynamics by comparing outcomes with and without PCM integration. The transient thermal problem is accurately tackled using the FEM, employing the evaluated effective constitutive parameters of the homogenized composite to minimize computational effort. The results indicate a notable decline in the highest temperatures of the battery pack, leading to a reduction of about 14 °C at the specific moment when the phase change material fully transitions into its liquid form. The obtained results emphasize the effectiveness and practical feasibility of the proposed thermal management strategy. The modeling approach presented provides a robust tool with significant efficiency in reducing computational time for analyzing the thermal behavior of large models, as the utilization of the homogenization technique notably decreases the computational time.

Effective properties of masonry structures and macro-model analysis with experimental verification

Masonry structures are the most prevalent type of buildings worldwide, and a significant portion are situated in seismic-prone areas. Thus, detailed information regarding their seismic strength and vulnerability is needed. The complexity of studying masonry structures lies in defining accurate and efficient models for representing masonry walls. In this context, there is a need for simplified methods that allow the modeling of masonry walls within a 3D structure. This work presents a methodology to define effective masonry properties from numerical analyses on representative volumes, using a damage model informed by experimental tests on units and mortar. These effective material properties serve as input parameters to model masonry walls within a macro-model approach, aiming to accurately capture the in-plane behavior and damage mechanisms with limited computational cost. The methodology is verified with experimental results and applied to real case studies in Cuenca, Ecuador.

Bending-based solution methodology using eigenvalue-eigenvector approach for analysis of foldable reinforced Golf Clubs cylindrical shell

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.

The role of machine learning for insight into the material behavior of lattices: A surrogate model based on data from finite element simulation

In recent years, lattice structures have gained extensive attention due to their unique properties and great potential in various fields. Their effective material properties can be obtained by several means, e.g., numerical homogenization methods, finite element (FE) simulations, and experiments. Numerical homogenization methods involve certain assumptions, and thus, their applications are limited to those lattice structures satisfying all assumptions. On the contrary, although the FE simulations and experiments can be performed for all lattice structures, they are more time-consuming and tedious than the numerical homogenization methods, especially for lattice structures with complex geometry. In this study, a surrogate model is presented to address all the drawbacks mentioned above. More precisely, the effective elastic modulus of two-dimensional lattice structures with triangular unit cells is predicted by a surrogate model trained with the random forest algorithm. The dataset is generated from FE simulations. Several geometric details along with the elastic modulus of the parent material are selected as input features. These input features are varied to cover a wide range of lattice structures encountered in engineering applications. The correlation between input features is investigated to test their independence. Furthermore, the contribution of each input feature to the prediction of the surrogate models is also thoroughly examined. The accuracy of the proposed surrogate model is evaluated through comparisons with FE simulations, numerical homogenization methods, and experiments for untrained datasets.