Volume Fraction Of Layer Research Articles

Thermal and thermo-mechanical post-buckling analysis of GNP-reinforced composite laminated plates

This research utilizes isogeometric analysis (IGA) method to analyze buckling and post-buckling responses of composite laminated plates embedded with graphene nanoplatelets (GNPs) subjected to three-dimensional (3D) conduction of heat or combined 3D heat conduction and mechanical edge compression. A formulation to determine temperature profile produced by 3D conduction of heat in the GNP-reinforced laminate is established, and a new function with smooth transition form of GNP volume fraction across the thickness is presented for dictating the volume fraction of layer. Shear deformable quasi-3D theory with the von Kármán type nonlinearity which takes initial geometric deformation and thermal effect into consideration is employed to construct the nonlinear equilibrium states. Four types of GNP arrangements encompassing uniform, O, X and V shapes are considered. The IGA approach presented, through the benchmark test, is evidenced to estimate the thermal buckling temperature accurately and to successfully trace the thermal post-buckling path. Additional parametric study is carried out to scrutinize the thermal and the thermo-mechanical post-buckling features of the GNP-reinforced composite laminated plates, and the new findings are sure to be served as the benchmark solutions.

Data-driven shear capacity analysis of headed stud in steel-UHPC composite structures

This study employs machine learning (ML) techniques for shear capacity analysis of headed stud in steel-UHPC composite structure. 194 experimental and numerical results of push-out tests are collected and serve as the dataset for ML models training and testing. Six ML algorithms are implemented to train ML models. Comparison analysis is conducted to compare the performance of three empirical formulae and ML models. The results demonstrate that both the Random Forest and eXtreme Gradient Boosting Trees (XGBoost) models exhibit excellent performance, surpassing an R2 value of 97 % on both training and testing datasets. In contrast, the empirical formulae perform less effectively. Besides, the study incorporates the Shapley additive explanations algorithm to ranking the importance of each feature, and carried out parametric analysis to investigate the correlation between each feature and shear capacity using all samples in the collected dataset. Notably, the most influential variables include diameter and ultimate strength of the headed studs, followed by stud height and thickness of UHPC slab. Cover thickness of UHPC layer and steel fiber volume fractions shows little influence on the shear capacity. Furthermore, based on findings of parametric analysis, design recommendations are provided to avoid shear capacity reduction caused by group effect of studs and UHPC damage. Finally, a user-friendly interactive software is developed and provided to facilitate the shear capacity prediction and design of headed studs in steel-UHPC composite structures.

Dynamic topology optimization of two-phase viscoelastic composite structures considering frequency- and temperature-dependent properties under random excitation

This article proposes an efficient optimum design method of constrained layer damping (CLD) plates characterized by non-proportional damping subjected to random excitation. Considering frequency and temperature dependence, a two-phase viscoelastic composite material composed of stiffness-phase and damping-phase materials is used as the damping layer. The pseudo excitation and hybrid expansion methods are adopted to compute the random responses at the specified frequency intervals as the objective functions. The sensitivity analysis is performed through the adjoint vector method. The similarity index is defined to distinguish the various optimal layouts quantitatively. Several numerical examples clearly demonstrate the robustness and effectiveness of the proposed method, highlighting a remarkable improvement of over 60% in computational efficiency. Furthermore, it is proved that, when subjected to broadband random excitation, the damping materials' temperature- and frequency-dependent properties are critical factors in obtaining accurate vibration responses and desirable optimal layouts. The effects of the layer thicknesses and volume fractions of composite structures on topology optimization are also discussed. The results indicate that both layer thickness and volume fraction can change the mechanical properties of the composite structure and further affect the distribution characteristics of the damping material.

Study on the mechanical properties and deformation mechanism of copper with different volume fractions of gradient structure

In this study, ultrasonic rolling process (USRP) were performed on the rolled copper samples (with an initial grain size of 11.4 μm) to obtain the gradient structure (GS), which comprises nanocrystalline layer (NL), deformed layer (DL), and center layer (CL). The different GS layer (NL and DL) volume fractions of samples were obtained by performing different passes of USRP after rolling, and the effect of the GS layer volume fractions on the mechanical properties was further studied. The morphology and structure of (unrolled, rolled and rolled + USRP) samples were characterized by electron backscattering diffraction (EBSD) and transmission electron microscope (TEM). In-situ tensile testing was used to investigate the tensile deformation behavior of the GS sample. The results show that the rolled + USRP (12 passes) sample with the thickest GS layer (volume fraction of 42%) has the greatest strength (yield strength (YS) 262 MPa and ultimate tensile strength (UTS) 325 MPa). The fine grains, dislocations and textures jointly strengthen the GS sample by increasing the force required for dislocation slip, and their contribution to YS is 51.3%, 44.4% and 4.3%, respectively. In addition, the nanocrystalline grains of GS layer make microcracks evenly distributed and hard to gather, to efficiently hinder cracks propagation and result in good ductility of GS samples. This study provides an effective method to obtain GS materials with good comprehensive properties and a deeper understanding of their deformation behavior and strengthening mechanism.

Parallel differential evolution paradigm for multilayer electromechanical device optimization

Design optimization of multilayer piezoelectric transducers is intended for efficient and practical usage of wideband transducers for fault diagnosis, biomedical, and underwater applications through adjusting layer thicknesses and volume fraction of piezoelectric material in each layer. In this context, we propose a parallel differential evolution (PDE) algorithm to mitigate the complexities of multivariate optimization as well as the computation time to achieve an optimized wideband transducer for the particular application. For lead magnesium niobate-lead titanate (PMN PT)- and PZT5h-based piezoelectric materials, the fitness function is formulated based on uniformity of mechanical pressure at the first three harmonics to achieve wide bandwidth in the required functional frequency range. It is carried out using a one-dimensional model (ODM), while input layer thicknesses and volume fractions of active material are evaluated using PDE. The simulation is performed on a parallel computing platform utilizing three different host machines to reduce computational time. Results of the proposed methodology for PDE are statistically represented in the form of minimum, maximum, mean, and standard deviation of fitness value, while graphically represented in terms of speedup and time. It can be observed that the execution time for parallel DE decreases with the increasing number of cores.

Computational Optimization of Sandwich Silicone Rubber Composite for Improved Thermal Conductivity and Electrical Insulation.

The efficient dissipation of heat has emerged as a crucial concern for modern electronic devices, given the continuous increase in their power density and consumption. Thus, the utilization of thermally conductive but electrically insulating silicone rubber composites as a thermal interface material has garnered significant interest. In this study, the effects of the filler volume fraction, filler orientation, layer volume fractions, layer configuration, and a number of layers on the thermal conductivity and electrical resistivity of silicone rubber composites were examined using a multiscale finite element modeling strategy. The results demonstrated that modification of the filler orientation can change the thermal conductivity by 28 and 21 times in the in-plane and through-thickness directions, respectively. The in-plane thermal conductivities of silicone rubber/boron nitride and silicone rubber/expanded graphite layers exhibit a percolation phenomenon at filler volume fractions of 35% and 30%, respectively. The electrical resistivity of the composite increases exponentially with a decrease in the number of layers.

Dynamic Topology Optimization of Constrained Damping Plates considering Frequency and Temperature Characteristics Based on an Efficient Strategy

The frequency- and temperature-dependent characteristics of viscoelastic materials significantly affect the vibration response of the damped composite structures. In this paper, an efficient strategy of hybrid expansion combined with dynamic reduction is developed to solve the steady-state response of the frequency- and temperature-dependent viscoelastic structure characterized by nonproportional system, and the sensitivity analysis is carried out based on the adjoint variable method. The similarity index is defined to distinguish the correlation among different design layouts. Two instances demonstrated the validity of the proposed approach. The findings indicated that a positive compromise between accuracy and efficiency can be achieved, and the computational time can be significantly reduced while ensuring the accuracy of the results. Furthermore, it has been discovered that the excitation frequency and temperature significantly impact the optimal configuration of damping material. The effects of layer thicknesses and volume fractions on optimization designs are also further investigated.

A multilayer piezoelectric nanogenerator based on PVDF and BaTiO3 nanocomposite with enhanced performance induced by simultaneously electrospinning and electrospraying

Piezoelectric materials have garnered significant interest owing to width range of applications in sensing and energy harvesting by converting environmental mechanical energy to electricity. Improving the performance of piezoelectric nanogenerators (PENGs) is an important challenge to develop these devices. Herein, a novel method was used to enhance the piezoelectricity of the PENGs based on PVDF NFs (polyvinylidene fluoride nanofibers) and BaTiO3 NPs (barium titanate nanoparticles) by simultaneously electrospinning of PVDF NFs and electrospraying of BaTiO3 NPs. Two set of nanogenerator devices were prepared which differ in piezoelectric layer arrangements and volume fraction of piezopolymer and piezoceramic parts. Results showed that, in case of simultaneously electrospinning and electrospraying (E/E), a significant increase in piezoelectric phase content and voltage output has been observed in comparison with the layer by layer arrangement. The improved piezoelctric performace may result from better dipole alignment facilitated by a more intense electric field during the simultaneously E/E process, along with heightened interactions between the two materials arising from enhanced contact in a multilayer configuration. Moreover, the optimum volume ratio of piezopolymer to piezoceramic to obtain the maximum output was 1.5 to 0.5. Therefore, simultaneously E/E effectively enhance the piezoelectric performance without having the common challenges in the electrospinning process of nanocomposites, as well as decreasing the total preparation time and simplifies the processing steps. Having such features, leads to hold great appeal of these nanogenerators for diverse applications.

Entropy generation minimization of hybrid nanofluid mixed convection flow in lid-driven square enclosure with heat-generating porous layer on inner walls

PurposeThis study aims to numerically scrutinize the entropy generation minimization and mixed convective heat transfer of multi-walled carbon nanotubes–Fe3O4/water hybrid nanofluid flow in a lid-driven square enclosure with heat generation in the presence of a porous layer on inner surfaces, considering local thermal non-equilibrium (LTNE) approach and the non-Darcy flow model.Design/methodology/approachThe dimensionless governing equations for hybrid nanofluid and solid phases are solved by applying the finite volume method and semi-implicit method for pressure-linked equations algorithm.FindingsThe roles of the internal heat generation in the porous layer, LTNE model and nanoparticles volume fraction on mixed convection phenomenon and entropy generation are introduced for lid-driven cavity hybrid nanofluid flow. Based on the investigation of entropy generation and heat transfer, the minimum total entropy generation and average Nusselt numbers are found at 1 ≤ Ri ≤ 10 where the effect of the forced and free convection flow directions being opposite each other is very significant. When considering various nanoparticle volume fractions, it becomes evident that the minimum entropy generation occurs in the case of φ = 0.1%. The outcomes of LTNE number reveal the operating parameters in which thermal equilibrium occurs between hybrid nanofluid and solid phases.Originality/valueThe analysis of entropy generation under various shear and buoyancy forces plays a significant role in the suitable thermal design and optimization of mixed convective heat transfer applications. This research significantly contributes to the optimization of design and the advancement of innovative solutions across diverse engineering disciplines, such as packed-bed thermal energy storage and thermal insulation.

Experimental study on insertion loss of air bubble layer in freestream flow

Air injection in water has several engineering advantages, such as an air lubrication system, cavitation control, and noise reduction. The present study investigates the effect of air injection rate and stream velocity on bubble layer volume fraction, thickness, and noise mitigation. The air bubble volume fraction is controlled through the injection rate of 2 to 25 SLPM at different stream velocities. The Froude number is in the range of 30.30 to 70.7. The image processing technique quantifies the air bubble projected void fraction and thickness. The air is injected through a multi-hole pipe placed on a modified NACA 0010 hydrofoil with a 100 mm chord length. The acoustic measurement system consists of a sound transmitter that projects sound waves at the frequency range of 7 to 50.5 [kHz], and on the opposite side of the air bubble layer, a hydrophone is placed to receive the transmitter sound wave. The results showed that the air bubble projected void fraction increased as the air injection and Froude number increased. Higher stream velocity promotes air bubble breaking and the formation of diverse air bubble patterns such as mono-dispersion bubbles and clustering bubbles. As the Froude number increases, the size of the bubble decreases. At various air injection rates and stream velocities, the thickness of the air bubble layer is found to be nearly constant. The bubble layer effectively reduces the noise in all frequency ranges of the present study. The sound pressure level (SPL) inhibition rate increases as the air bubble projected void increases. The insertion loss increases with stream velocity as higher flow velocity leads air bubbles to break and form a cluster of air bubbles, which is found to be more effective in reducing noise than a single bubble. Regardless of injection rate, the maximum insertion loss is 44 [dB] in a frequency of 20 [kHz] and Froude number 70.7.

Efficient multivariate optimization of an ultrasonic transducer with genetic parallel algorithms

Design optimization of a multilayer transducer is desired for flaw detection, biomedical and underwater applications by controlling layer thicknesses of active material and volume fractions of ceramic in each piezocomposite layer. To handle the computational complexity in solving such multivariate optimization and the complex nature of the problem, we propose a parallel genetic algorithm (GA)-based strategy. The complexity of the problem increases with the number of layers and layer-wise ceramic volume fraction to achieve an optimized transducer working efficiently in an operational frequency range as desired by the application specification. The fitness function is formulated based on the transducer response in terms of about the same value of pressure magnitude at the first three harmonics at functional frequencies. The fitness value is computed using a one-dimensional model (ODM) for PMNPT, PZT4d, and PZT5h-based materials initially, while input layer thicknesses and volume fractions are evaluated through GAs and passed to ODM. The overall scheme is maintained through parallel GAs. The simulation is performed by using 1, 4, 6, and 8 core machines to reduce time complexity. The results for parallel GA-ODMs are statistically represented in the minimum, maximum, mean and standard deviation of fitness, while graphically represented for speedup and time.

Fatigue life prediction approach for through-hole of needled ceramic matrix composite based on volume fraction

An applied approach for predicting the fatigue life of the through-hole for needled ceramic matrix composite was proposed by using the 0° layers volume fraction and the fatigue notch factor, which can be applicable for the needled composite with different lamination types. In the proposed approach, the fatigue limit and stress-life (S–N) curve of the needled ceramic matrix composite with different 0° layer volume fractions were estimated by interpolation method first. On this basis, combined with the fatigue notch factor determined by the smooth and through-hole specimens with arbitrary 0° layer volume fraction, the fatigue life of the through-hole can be predicted. By comparing the predicted lives with the experimental lives, the proposed fatigue life prediction approach has high prediction accuracy.

Multi-flow channel proton exchange membrane fuel cell mass transfer and performance analysis

This paper presents a study on the proton exchange membrane fuel cell (PEMFC) with a high humidity three-dimensional two-phase multi-channel model using COMSOL. The effects of gradient porosity in the gas diffusion layer (GDL) and gradient electrolyte volume fraction in the catalyst layer (CL) in the Y-direction on oxygen distribution, liquid water removal, current density surface area reaction rate (SCS), and current density magnitude of PEMFC are investigated. The results indicate that an appropriate gradient porosity in the GDL can improve the performance of PEMFC, especially in terms of oxygen distribution. Similarly, an appropriate gradient electrolyte volume fraction in the CL can enhance the current density uniformity. In addition, an improved multi-objective genetic optimization algorithm (RONSGA-II) is proposed in Chapter 4, along with an optimization method based on neural networks and RONSGA-II. As an example, the gradient porosity in the GDL in the Y-direction is optimized for current density and water removal. The optimized current density is increased by 1.22%, and water removal performance is improved by 16.67%.

The mechanical performance of optically tuned ceramic nanomultilayers

Multifunctional optical nanomultilayers (NMs) are needed for a wide array of applications, ranging from optical windows to electronic screens. Since the individual material constituents in optical coatings are often selected only for their desirable optical properties, mechanical characterization of the optical nanomultilayers is typically limited. Here, AlN/SiO2, TiO2/SiO2, and AlN/Al2O3 nanomultilayers synthesized in non-optimized and optimized optical performance layer configurations are tested using microtensile, nanoindentation, and pillar splitting techniques to highlight the effects of optical optimization on mechanical performance. Trends within each type of test and across all deformation modes reveal that layer thickness, volume fraction, and interfacial crystallinity can be viewed as controlling features for optical and mechanical performance, although their correlation may vary. It was observed that both configurations of the AlN/Al2O3 NMs exhibit the highest mechanical performance across all three testing techniques with an average experimental transmittance of 93.8% for the optimized layer configuration. Overall, the results from this expanded view of mechanical properties in ceramic optical nanomultilayers suggest the possibility of tuning film characteristics for joint optimization of opto-mechanical nanomultilayered coatings.

Biophotonic sensor for swift detection of malignant brain tissues by using nanocomposite YBa2Cu3O7/dielectric material as a 1D defective photonic crystal

In the present research work we have theoretically examined the biosensing capabilities of proposed one dimensional defective photonic crystal for swift detection of malignant brain tissues. The transfer matrix formulation and MATLAB computational tool have been used to examine the transmission properties of proposed structure. The identical buffer layers of nanocomposite superconducting material have been used either side of cavity region to enhance the interaction between incident light and different brain tissue samples poured into the cavity region. All the investigations have been carried out under normal incidence to suppress the experimental liabilities involved. We have investigated the biosensing performance of the proposed design by changing the values of two internal parameters (1) the cavity layer thickness (d4) and (2) volume fraction (η) of nanocomposite buffer layers one by one to get the optimum biosensing performance from the structure. It has been found that the sensitivity of the proposed design becomes 1.42607 μm/RIU when the cavity region of thickness 15dd is loaded with lymphoma brain tissue. This value of sensitivity can be further increased to 2.66136 μm/RIU with η = 0.8. The findings of this work are very beneficial for designing of various bio-sensing structures composed of nanocomposite materials of diversified biomedical applications.

A longitudinal gradient architecture achieves better tensile properties in Ti6242 alloy

Simultaneous increase in strength and ductility is obtained in Ti6242 alloys using a longitudinal gradient structure. Such architecture demonstrates strain hardening regarding the gradient layer's volume fraction (Vf). The maximum strain hardening is produced in the freestanding gradient layer (Vf = 100%). An extra strain hardening evidenced by the increased back stress occurs in gradient samples, which partly accounts for the concurrently improved properties. Additionally, more boundaries of the α/β plates in lamellar structure and increased dislocations in the primary α phase (αp) are responsible for the enhanced strength. In the gradient layer, such microstructural characteristics, including significant thinning of the β plates, the locally disappeared boundaries of αp and transformed β structure (βt), and the reduced property difference between deformed αp and βt, contribute as well on the ductility improvement. This work provides a guideline for manufacturing high-performance Ti alloys via microstructural regulation or gradient architecture.

In vitro assessment of calcite-hydroxyapatite conversion of 3D-Printed cube honeycombs in dilute phosphate solutions in the neutral pH range

Calcite particles (Source; CaCO3, ∼0.4 μm in size) were 3D-printed into cube honeycombs (honeycombs) with ∼0.7 mm thick struts and ∼0.6 mm cellular window opening. The sintered honeycombs, regardless of the presence of a sintering aid in the printing slurry, gave ∼3 MPa or more in the compressive stress, which exceeded that of trabecular bone. The conversion of calcite to hydroxyapatite (HAp) was assessed in 0.1 M K2HPO4 (pH: 7.0 or 7.4) at 20 °C–80 °C due to the X-ray diffraction intensity of the calcite and HAp peaks, surface microstructure, and P(V) accumulation on the honeycomb strut surface. Although a premature HAp layer yielded on all samples within 1 h soaking, further conversion depended on the samples. The conversion continued on Source until the volume fraction of the HAp shell layer reached ∼35% (37 °C). It was hardly detected on the grains of sintered honeycombs (from the slurry with the sintering aid) within the whole soaking period (≤24 h). In contrast, the conversion on the sintered honeycombs (from the slurry without the aid) became vigorous when soaked for 5 h, and, it reached at 24 h the highest level that the as-printed honeycombs achieved. The critical factors controlling the conversion were calcite dissolution, the equilibria among the carbonate and phosphate ions, and the rates of migration of Ca(II) and P(V) through the inter-granular channels of pores within the struts. A particle stacking model was proposed for the most plausible interpretation of the present results.

Preparing Thick Gradient Surface Layer in Cu-Zn Alloy via Ultrasonic Severe Surface Rolling for Strength-Ductility Balance.

A gradient structure (GS) design is a prominent strategy for strength-ductility balance in metallic materials, including Cu alloys. However, producing a thick GS surface layer without surface damage is still a challenging task limited by the available processing technology. In this work, a gradient structure (GS) surface layer with a thickness at the millimeter scale is produced in the Cu-38 wt.% Zn alloy using ultrasonic severe surface rolling technology at room temperature. The GS surface layer is as thick as 1.1 mm and involves the gradient distribution of grain size and dislocation density. The grain size is refined to 153.5 nm in the topmost surface layer and gradually increases with increasing depth. Tensile tests indicate that the single-sided USSR processed alloy exhibits balanced strength (467.5 MPa in yield strength) and ductility (10.7% in uniform elongation). Tailoring the volume fraction of the GS surface layer can tune the combination of strength and ductility in a certain range. The high strength of GS surface layer mainly stems from the high density of grain boundaries, dislocations and dislocation structures, deformation twins, and GS-induced synergistic strengthening effect. Our study elucidates the effect of the thick GS surface layer on strength and ductility, and provides a novel pathway for optimizing the strength-ductility combination of Cu alloys.

Study on dynamic recrystallization-based microstructure evolution mechanism of 40Cr during strengthening grinding

Grind-strengthening represents a novel surface modification process that combines a precision removal process of material and the strengthening function of surface modification. The high heat and severe plastic deformation (SPD) of the ground superficial layer can induce the phase transformation and dynamic recrystallization (DRX) grain refinement behavior. Consequently, the prediction and control of the ground superficial layer microstructure is of considerable significance to improve the wear resistance and fatigue resistance performance of parts. Firstly, the dynamic mechanical properties at high temperature and shock compression were tested by the split Hopkinson pressure bar (SHPB) experiment for 40Cr steel. The material's constitutive relations, critical strain and DRX model can be determined. Subsequently, the finite element (FE) method was proposed to predict the temperature and strain distribution of the ground strengthening layer. The DRX volume fraction and grain size of the ground superficial layer can be realized via Abaqus/explicit user subroutine VUHARD. Finally, a phenomenological simulation of the ground strengthening layer microstructure is realized utilizing the cellular automata (CA) method combined with FE analysis results. With the help of grind-strengthening experiments, the gradient distribution of grain refinement layer at different cutting depths is consistent with the prediction results. The proposed DRX and microstructure predicted model can provide theoretical support for the surface strengthening of steel grinding. The modification behavior of the gradient refinement induced by grind-strengthening has significant application potential in the fields of transmission parts such as gears and shafts.

Enhanced strength-ductility of CoCrFeMnNi high-entropy alloy with inverse gradient-grained structure prepared by laser surface heat-treatment technique

The inverse gradient-grained CoCrFeMnNi high-entropy alloy with a desirable mechanical property that evades the strength-ductility trade-off is fabricated by the process of cold rolling and subsequent laser surface heat-treatment. Due to the gradually decayed thermal effect along with the thickness, the grain size increases from the hard core to the soft surface in terms of the inverse gradient-grained sample, which is in good consistent with the microhardness profiles. The hetero-deformation induced strengthening and strain hardening caused by the inverse gradient-grained structure improve the strength-ductility combination, as well as the high-order hierarchal nanotwins due to the enhanced interaction with dislocations. For the laser surface heat-treatment technique, the strength and ductility are significantly increased by enlarging the microhardness difference and decreasing the thermal stress. Considering the high volume fraction of gradient-grained layer and a great deal of high-order hierarchal nanotwins in the central region, the laser surface heat-treatment technique is a promising way to produce the gradient-structured materials without thickness limitation.