Take in to account of metal foams properties like energy absorption; they have several implementations. The complication of foam structures leads difficulties in investigation of elastic and plastic modulus. In the present research, porosity of foam are modeled and analyzed, numerically. In this context, MATLAB and JavaScript have been developed for geometrical modeling of porous materials considering density, radius, and random distribution of porous. Several porous configurations are simulated using periodic boundary conditions on Micro/Meso Scale in order to numerically calculate their elastic mechanical properties like Young’s modulus and shear modulus as a function of the porous configuration. The porous are distributed randomly and the effect of configuration parameters (like shape, number, size) are investigated on elastic modulus. In order to simulate more accurately, porous characteristics were investigated using SEM experimental tests. Eventually, the calculated effective constants of porous materials are compared with numerical and experimental literatures. This comparison demonstrates that the proposed method can accurately model high range of porosity (from 5% to 65%) and estimate the effective constant of porous materials in 3 directions including of (E1, E2, E3, G12, G13, G23).

The present study investigated mechanical properties such as Young's modulus and tensile strength of aluminum nanocomposite reinforced with defective graphene with vacancy and hole defects under uniaxial tension using molecular dynamics simulation. Also, the effect of the number of graphene layers in a constant volume ratio on the mechanical behavior of the nanocomposite has also been obtained. This simulation was done with the help of the LAMMPS open-source package by modeling a periodic system with NVE and NPT ensembles. The AIREBO and MEAM potentials were used to describe the interaction of carbon and aluminum atoms, respectively, and Lennard Jones potential was used for the interaction between these atoms. The obtained results show that adding a single layer of graphene to the structure of pure aluminum has improved Young's modulus and tensile strength of pure aluminum by 220 and 320%, respectively. In addition, it is observed that the effect of pinhole and vacancy defects on Young's modulus and tensile strength is non-linear and has a decreasing trend.

Determining the modulus of elasticity for soil is crucial in geotechnical engineering when conducting stress-deformation analyses. However, due to the difficulty involved in calculating this parameter, as well as the fact that the modulus of elasticity for soil is nonlinear in nature, there is often uncertainty surrounding its value. A study was therefore conducted to investigate these uncertainties and their impact on geotechnical analyses and plans. The study involved modeling and numerically analyzing a deep drilling guard structure using the anchoring method. To obtain the necessary information, two projects – depth and guard structure, which were both undertaken by Jahan Mall and Baran - in Mashhad were selected as case studies. In this study, the Jahan Mall project pit was analyzed using both two- and three-dimensional numerical models. Four different models were used: Moore-Coulomb (MC), hardening soil (HS), hardening soil with small strain stiffness (Cysoil HSS), and a newly developed nonlinear model based on the Moore-Coulomb model. To carry out the analysis, information obtained from barometric tests, standard penetration tests, and shear wave propagation was used. The results of the analysis were compared with each other and with the monitoring data. It was found that for the Moore-Coulomb behavior model, the pressure modulus (Ep) should be corrected to three to five times its original value in order to obtain accurate results. However, for the Cysoil HSS, HS models, and the newly developed model, there was no need to correct the pressurometric data or shear wave propagation. Additionally, it was determined that while no correction is necessary when using standard penetration numbers, an appropriate relationship should be used to convert them into the modulus of elasticity. Based on these findings, the Gud Baran project was analyzed, and it was concluded that the newly developed model and method for converting standard penetration numbers can be applied broadly and produce desirable results.

The resilient modulus (MR) of road materials is one of the most important parameters in the analysis and design of pavement. This parameter is used in both empirical methods and mechanistic-empirical methods as the main parameter for expressing the stiffness and behavior of road construction materials. To determine this parameter in the laboratory, it is necessary to perform a dynamic tri-axial loading test under various confining and deviator stresses, which is a time- and cost-intensive approach. In this paper, a wavelet neural network (WNN) hybridized with the teacher learning based optimization (TLBO) algorithm was used to model the MR of unbound subbase materials. The input variables included maximum dry density, uniformity coefficient, curvature coefficient, percent passing No. 200 sieve, confining stress, and deviator stress and output variable was resilient modulus of the unbound subbase materials. The results of this study indicate that increasing the number of neurons in the hidden layer to more than 20 neurons has little effect on increasing the accuracy of the wavelet neural network and the Mexican Hat wavelet function has the best result in predicting the resilient modulus. The results of this study also indicate that the WNN-TLBO method is more accurate than the ANN method in predicting the MR of unbound subbase materials. External validation results indicate that the WNN-TLBO method satisfy all the necessary criteria, which indicates the high predictive potential of this method. The results of sensitivity analysis indicate that the degree of importance of the confined stress is higher than other variables for predicting the resilience modulus. A parametric analysis was also done to study the effects of each input variable on the MR.

In the present investigation, a detailed numerical investigation of the flow and heat transfer characteristics of a channel with an elastic fin (vortex generator) and an elastic wall has been carried out using finite element method. The Fluid-Structure Interaction (FSI) model is used to capture the interaction between the fluid and the solid structure. A sinusoidal time dependent velocity profile has been imposed at the inlet of the channel and the right half of the upper wall of the channel is heated and exposed to constant temperature boundary condition. Due to the sinusoidal velocity profile at the inlet, the elastic fin oscillates periodically and act as a vortex generator, which causes more turbulence in the flow. The obtained results showed that the Nusselt number over the heated wall is affected by the position of the flexible fin, height of flexible fin and elasticity modulus of elastic fin. Moreover, due to the elasticity of the elastic wall and sinusoidal behavior of the inlet velocity, the elastic wall oscillates periodically upward and downward. The Nusselt number values over the heated wall are increased with decrease of the elastic modulus value of the elastic wall. However, the decrease in elastic modulus value of the elastic wall contributes to an increase in the pressure drop inside the channel. It should be added that the interplay between the fluid motion and the deformable structures leads to enhanced turbulence, as the flexible fin and elastic wall introduce additional disturbances and fluctuations into the flow regime. Consequently, this heightened turbulence level has profound implications for heat transfer processes within the system.

Brake noise is often caused by the coupling of the natural frequencies of the disc and pad. To prevent this, it is important to control the natural frequencies of these components, hence, the dispersion of natural frequency values is a critical factor in brake noise determination. This paper examines how the brake pad's natural frequencies and mode shapes are affected by its friction material properties, such as Poisson's ratio, Young's modulus, and shear modulus in different directions. Two brake pad designs from Land Rover are modelled and analysed using finite element analysis (FEA) and experimental modal analysis (EMA). A machine learning algorithm based on multiple-features linear regression is used to identify the main friction material parameters and their relationship to the natural frequencies. The results show that increasing the transverse Young's modulus or decreasing the longitudinal Young's modulus, shear modulus, or Poisson's ratio in all directions can increase the natural frequencies. Consequently, the paper suggests that Poisson's ratio and transverse Young's modulus should be considered when selecting friction compounds for brake pads.

Seismic designs and numerical analyses required fundamental parameters such as damping ratio and shear modulus. In this study, large-scale triaxial cyclic tests were used to investigate the dynamic properties of limestone ballast and electric arc furnace (EAF) slag ballast. The term ‘shear stiffness’ is typically reported in a normalized form using shear modulus. As the laboratory test results showed, an increase in confining pressure, loading frequency and anisotropy raises the shear modulus of materials. Shear modulus and damping ratio values do not appear to be significantly affected by an increase in loading cycles. Loading frequency plays the most significant role in changing damping ratio values. An adaptive neuro-fuzzy inference system (ANFIS) was also used to predict the normalized shear modulus and the damping ratio in this study. The results of the developed model were consistent with those of the laboratory tests. Moreover, the relations among the dynamic properties were estimatedly determined using the nonlinear regression method.

Multiscale modeling (MM) has broadened its scope to encompass the calculation of mechanical properties, with a particular focus on investigating how the dimensions of single-walled carbon nanotubes (SWCNTs), specifically their diameters, affect the mechanical properties (Longitudinal and Transverse Young’s modulus) of simulated nanocomposites through Molecular Dynamics (MD) simulations. The MD method was employed to construct nanocomposite models comprising five different SWCNTs chiralities: (5, 0), (10, 0), (15, 0), (20, 0), and (25, 0), serving as reinforcements within a common Polymethyl methacrylate (PMMA) matrix. The findings indicate a correlation between the SWCNT diameter increase and enhancements in mechanical and physical properties. Notably, as the diameter of SWCNTs increases, the density, Longitudinal Young’s modulus, Transvers Young’s Shear modulus, Poisson’s ratio, and Bulk modulus of the simulated nanocomposite transition from (5, 0) to (25, 0) by approximately 1.54, 3, 2, 1.43, 1.11, and 1.75 times, respectively. To corroborate these results, stiffness matrices were derived using Materials Studio soft ware.

The deformation modulus of rock mass is necessary for stability analysis of rock structures, which is generally estimated by empirical models with one to five input parameters/indexes. However, appropriate input parameter participation to establish a sound basis for a reliable prediction has been a challenging task. In this study, the concept of the principal input parameters was developed based on an analytical method with an emphasis on in situ stress. Based on analytical methods, Young’s modulus of intact rock, the joint’s shear and normal stiffness, joint set spacing, and in situ stress are introduced as the main principal input parameters. A review of seventy empirical models revealed that most of them suffered from a lack of analytical parameters. Due to considering practical issues, the geological strength index (GSI) is replaced with joint set spacing; moreover, the in situ stress effect is perceived by combining Young’s modulus and joint stiffness with specific confining pressure and normal stress, respectively. The integration of the analytical base input parameters and practical issues enhanced the reliability of empirical models due to the reasonable prediction of the deformation modulus to numerical or analytical deformability analysis.

Composites hold significant importance in the world of engineering and everyday human life, with their usage evident in various industries such as automotive, military, medical, and others. This research investigates the mechanical properties, impactability properties, and energy absorption of aluminum-glass epoxy composite samples manufactured through vacuum infusion. To investigate the effect of plasma treatment on experimental results, the composite samples were divided into two categories: plasma-treated and untreated. The tests conducted include standard tensile test, three-point bending test, and free-fall impact test. This research measures the elastic modulus, yield stress, maximum length change, and toughness from the standard tensile test; bending strength and bending elastic modulus from the three-point bending test; and energy absorption parameters and impact resistance at different speeds from the free-fall impact test. The results showed that composites manufactured using the vacuum infusion method exhibit significantly better mechanical and impactability properties compared to metal samples. Additionally, plasma treatment improves the yield stress by 8.1%, the elastic modulus by 7%, the ultimate stress by 16.3%, the bending strength by 2.3%, and the bending elastic modulus by 3% compared to the untreated composite samples.