Elastic Parameters Research Articles

A simulation-optimization approach for economic assessment of an imperfect serial production management under uncertainty

ABSTRACT One of the critical quandaries in real-world production management systems is uncertainty in the product demand, which is closely associated to the product price. This uncertain behavior of demand affects production decisions in a system. In this context, this study develops a decision support framework for an imperfect serial production management system under uncertainty. The proposed framework is analyzed considering price-dependent uncertain demand and random defective rate in the system, thus considering both internal and external uncertainties of the system. Three distinct production models are formulated considering different types of uncertain relations among the product demand and market price. Closed form solutions of the decisions are obtained through hybrid of simulation and analytical optimization and are tested through an experimental case analysis. @RISK of Palisade Suite is utilized for simulation and to capture the uncertainty in defective proportion and demand elasticity parameters by creating several possibilities.

Research on a Calculation Method for the Horizontal Displacement of the Retaining Structure of Deep Foundation Pits

The precise calculation and effective control of the horizontal displacement of deep foundation pit retaining structures are critical for foundation pit support design and construction. Based on stress–strain linear elastomer theory and considering the deformation coordination between an enclosure wall and its internal support member, a formula for the redundant restraint force acting on the retaining wall was derived through the unit load method and the principle of elastic superposition. Moreover, a method for calculating the horizontal displacement of the retaining structure of a deep foundation pit was formulated, which is convenient for engineering applications. The method can also be used to calculate the horizontal displacement of cantilevered and anchored retaining structures when the loading conditions of the deep foundation pit and the relevant parameters of the enclosure structure are known. A case study was conducted on a standard section with an excavation width H of 19.3 m and an excavation depth h of 17.8 m. The structural parameters of the enclosure wall, along with the elastic support stiffness coefficient and soil layer parameters of the pit, were inputted into a MATLAB calculation code. Then, four internal support constraint forces Fi and the calculated values for the horizontal displacement of the enclosure wall were obtained after running the code. The calculated curve closely matched the curve of values measured in the field. The horizontal displacements of the top of the wall of several cement–soil gravity enclosure structures mentioned in the literature were also calculated. The results of these calculations were then compared with the measured data and corresponding data from the literature. The examples provided clear evidence demonstrating that the proposed method is highly reliable for calculating the horizontal displacement of deep foundation pit enclosure structures.

Sub-global equilibrium method for identification of elastic parameters based on digital image correlation results

In this work, a new, simple method is presented, which enables identification of material properties of solids basing on the digital image correlation (DIC) measurements. It may be considered as a simplified alternative of low computational complexity for the well-known finite element model updating (FEMU) method and virtual fields method (VFM). The idea of the introduced sub-global equilibrium (SGE) method is to utilize the fundamental concept and definition of internal forces and its equilibrium with appropriate set of external forces. This makes the method universal for the use in the description of a great variety of continua. The objective function is the measure of imbalance, namely the sum of squares of residua of equilibrium equations of external forces and internal forces determined for finite-sized part of the sample. It is then minimized with the use of the Nelder–Mead downhill simplex algorithm. The efficiency of the proposed SGE method is shown for two types of materials: 310 S austenitic steel and carbon-fiber-reinforced polymer (CFRP). The proposed method was also verified based on FE analysis showing error estimation.

Experimental investigation of pore-filling substitution effect on frequency-dependent elastic moduli of Berea sandstone

SUMMARY Based on both forced oscillation and ultrasonic pulse transmission methods, we investigated solid pore infill influences on rock elastic moduli in a broad frequency range $[ {1 - 3000,\,\,{{10}^6}} ]$ Hz for different differential pressures. For a Berea sandstone sample, filled sequentially by solid (${22\,\,^{\rm{o}}}{\rm{C}}$), quasi-solid (${26\,\,^{\rm{o}}}{\rm{C}}$) and liquid (${34\,\,^{\rm{o}}}{\rm{C}}$) octadecane, a frequency-dependence was found for the Poisson's ratio, Young's modulus and bulk modulus, nevertheless, these elastic parameters were strongly suppressed by increasing pressures. Experimental measurements showed that shear wave velocity and modulus of solid-octadecane-filled samples are significantly larger than those of the dry and liquid-octadecane-filled ones, implying the potential stiffening effects related to solid infill in compliant pores. A three porosity structure model, which describes the solid stiffening effects related to equant, compliant and the intermediate pores with aspect ratios larger than those of compliant pores but much less than those of stiff pores, was used to compare against the experimentally measured elastic properties for octadecane pore infill, together with several other fluid/solid substitution theories. The agreement between experimental measurements and theoretical predictions is reasonably good for the sandstone tested, providing that the three porosity model can be applied for pressure- and frequency-dependent elastic moduli estimations for a viscoelastic pore-infill-saturated sandstone. Evaluating the combined squirt flow mechanism responsible for the observed moduli dispersion and attenuation is of great importance to reduce potential errors in seismic AVO inversion and 4-D seismic monitoring of gas-hydrate or bitumen-saturated reservoir, especially for reservoir rocks with complex microstructures and heterogeneous pore types.

Magneto Axisymmetric Vibration of FG-GPLs Reinforced Annular Sandwich Plates with an FG Porous Core Using DQM and a New Shear Deformation Theory

Based on the differential quadrature procedure (DQP), the vibrational response of functionally graded (FG) sandwich annular plates enhanced with graphene platelets (GPLs) and with an FG porous core is illustrated in this paper. The current annular plate is assumed to deform axisymmetrically and expose to a radial magnetic field. The Lorentz magnetic body force is deduced via Maxwell’s relations. The effective physical properties of the upper and lower layers of the sandwich plate are obtained by employing the Halpin–Tsai model. Our technique depends on a new four-unknown shear deformation theory to depict the displacements. In addition, the motion equations are established via Hamilton’s principle. The motion equations are solved by employing the DQP. In order to study the convergence of the DQ method, the minimum number of grid points needed for a converged solution is ascertained. In addition, the current theory’s outcomes are compared with those of previous higher-order theories. The effects of the porosity distribution type, porosity factor, GPLs distribution pattern, GPLs weight fraction, inner-to-outer radius ratio, outer radius-to-thickness ratio, magnetic field parameters, core thickness, and elastic substrate parameters on the nondimensional vibration frequencies are discussed.

Pre-stack seismic inversion based on model-constrained generative adversarial network

Pre-stack seismic inversion usually uses various traditional algorithms to estimate elastic parameters such as P-wave velocity, S-wave velocity, and density. It is hard to derive accurate elastic parameters due to their non-uniqueness and high dimensionality between elastic parameters and seismic data, the calculation of elastic parameters is inaccurate. Convolutional Neural Networks (CNNs) have high-dimensional feature space mapping capabilities, which are utilized to establish mapping relationships between seismic data and elasticity parameters. However, their effectiveness is greatly affected by label data, and at the same time, due to the lack of enough label data, resulting in a low degree of fitting between prediction results and real data. In addition, conventional seismic inversion methods based on CNNs lack physical model constraints, resulting in low accuracy and poor interpretability of prediction results. We propose a Cycle-consistent Generative Adversarial Network based on a geophysical mechanism (SeisInv-CycleGAN). Deterministic inversion results and labeled data are combined into hybrid geophysical data as a training set of SeisInv-CycleGAN with geophysical constraints. At the same time, the residual (seismic loss) between the seismic data synthesized by forward modeling and the actual data is used as part of the loss function. The SeisInv-CycleGAN does not require building an initial model, and it can achieve higher accuracy in prediction results with a small amount of labeled data.

Bayesian linearized amplitude variation with offset and azimuth inversion and uncertainty analysis in horizontal transversely isotropic media

AbstractThe stratum can be modelled as a horizontal transversely isotropic medium when a single set of vertically parallel fractures embedded in an isotropic background medium, which facilitates efficient study for fractured reservoirs. Elastic parameters and fracture weaknesses are important parameters to describe the characteristics of fractured reservoirs, and seismic inversion plays a significant role in parameters estimation. The commonly used deterministic inversion methods do not fully utilize the prior information and fails to present the uncertainty analysis of inversion results. To address these shortcomings, we propose a Bayesian linearized amplitude variation with offset and azimuth inversion method tailored for horizontal transversely isotropic media, enabling a more robust analysis of uncertainty. Within the framework of Bayesian inversion, the proposed method successfully derives analytical expressions for the posterior mean and covariance of both elastic parameters and fracture weaknesses. The response characteristics of the anisotropic reflection coefficient are analysed, and it is found that the perturbations of elastic parameters have a greater effect on reflection coefficient compared to fracture weaknesses. Synthetic data examples confirm that the accuracy of estimated P‐ and S‐wave velocities and density surpasses that of fracture weaknesses, and the proposed method still performs well for the case of moderate noise. A field data example demonstrates that the inverted profiles agree well with the logging curve, and the estimated fracture weaknesses display significantly high values in the reservoir area. The estimated reservoir parameters not only contribute to a more accurate representation of the fractured gas‐bearing reservoir but also provide insights into the target gas reservoir through its posterior distribution. Both synthetic and field data examples demonstrate the stability and reliability of the proposed method in characterizing fractured reservoirs. We determine that the proposed method provides an available tool for nuanced evaluation of uncertainty for the inversion results, and it is helpful for the fine description of fractured hydrocarbon‐bearing reservoirs.

Multi-task learning for seismic elastic parameter inversion with the lateral constraint of angle-gather difference

Pre-stack seismic inversion is an effective way to investigate the characteristics of hydrocarbon-bearing reservoirs. Multi-parameter application is the key to identifying reservoir lithology and fluid in pre-stack inversion. However, multi-parameter inversion may bring coupling effects on the parameters and destabilize the inversion. In addition, the lateral recognition accuracy of geological structures receives great attention. To address these challenges, a multi-task learning network considering the angle-gather difference is proposed in this work. The deep learning network is usually assumed as a black box and it is unclear what it can learn. However, the introduction of angle-gather difference can force the deep learning network to focus on the lateral differences, thus improving the lateral accuracy of the prediction profile. The proposed deep learning network includes input and output blocks. First, angle gathers and the angle-gather difference are fed into two separate input blocks with ResNet architecture and Unet architecture, respectively. Then, three elastic parameters, including P- and S-wave velocities and density, are simultaneously predicted based on the idea of multi-task learning by using three separate output blocks with the same convolutional network layers. Experimental and field data tests demonstrate the effectiveness of the proposed method in improving the prediction accuracy of seismic elastic parameters.

The Effect of Hyperelasticity and Nonlinearity on the Dynamic Behaviors of Hyperelastic Functionally Graded Beams on Nonlinear Elastic Foundation

Hyperelastic functionally graded materials have a wide range of application prospects in soft robotics and biomedical fields. This paper investigates the nonlinear free and forced vibrations of a hyperelastic functionally graded beam (HFGB) based on higher-order shear deformation beam theory. The geometrical nonlinearity is considered by using the von-Kármán’s nonlinear theory. The three-material-parameter free energy function named as Ishihara model is employed to characterize the hyperelastic material. The power-law gradient form along the thickness direction is adopted. The HFGB is resting on the elastic foundation. The Winkler, Pasternak and nonlinear stiffness coefficients are considered. The time-harmonic external force is applied to the HFGB. The nonlinear governing equations for the vibration of the HFGB are derived by using Hamilton’s principle, and are subsequently transformed into ordinary differential equations via Galerkin’s method. The nonlinear free vibration and primary resonance of the HFGB are investigated analytically by employing the extended Hamiltonian method and multiple scales method, respectively. The results indicate that the power-law index, slenderness ratio, material properties, and elastic foundation parameters have significant influences on the nonlinear frequency of free vibration as well as the frequency–response and force–response curves of forced vibration. The phase plane method is employed to analyze the system’s stability states under various excitation amplitudes. The relative error between the results of the current computational model and the published literature is less than 0.1 percent.

Gas prediction in tight sandstones based on the rock-physics-derived seismic amplitude variation versus offset method

Estimating gas enrichments is a key objective in exploring sweet spots within tight sandstone gas reservoirs. However, the low sensitivity of elastic parameters to gas saturations in such formations makes it a significant challenge to reliably estimate gas enrichments using seismic methods. Through rock physical modeling and reservoir parameter analyses conducted in this study, a more suitable indicator for estimating gas enrichment, termed the gas content indicator, has been proposed. This indicator is formulated based on effective fluid bulk modulus and shear modulus and demonstrates a clear positive correlation with gas content in tight sandstones. Moreover, a new seismic amplitude variation versus offset (AVO) equation is derived to directly extract reservoir properties, such as the gas content indicator and porosity, from prestack seismic data. The accuracy of this proposed AVO equation is validated through comparison with the exact solutions provided by the Zoeppritz equation. To ensure reliable estimations of reservoir properties from partial angle-stacked seismic data, the proposed AVO equation is reformulated within the elastic impedance inversion framework. The estimated gas content indicator and porosity exhibit favorable agreement with logging data, suggesting that the obtained results are suitable for reliable predictions of tight sandstones with high gas enrichments. Furthermore, the proposed methods have the potential to stimulate the advancement of other suitable inversion techniques for directly estimating reservoir properties from seismic data across various petroleum resources.

Utilizing integrated neutron diffraction and elastoplastic self-consistent crystal plasticity model to quantitatively assess the strengthening mechanism in Al–12.5Ce and Al–12.5Ce–0.4Mg alloys

An integrated in-situ neutron diffraction and elastic plastic self-consistent crystal plasticity (EPSC-CP) modeling scheme is performed on a binary Al–12Ce alloy and a ternary Al–12Ce–0.4Mg alloys. Using this scheme, the constitutive parameters, i.e. elastic constants and slip system parameters of individual phases can be calibrated which can be used in microstructure-based CP models to predict materials performance. From this study, it is shown that the elastic constants of Al11Ce3 intermetallics calculated from density function theory calculation in the literature are rather accurate. When applied to the EPSC-CP model, the lattice strains of both the binary and ternary alloys are correctly predicted as compared with experiments, and large lattice strain differences between Al (100) plane and Al11Ce3 (010) plane are demonstrated. The slip system parameters calibrated by the scheme shows that the addition of 0.4 wt% Mg in the alloy has little influence on the critical resolved shear stress of initial dislocation glide in the Al matrix which caused plastic yield in the material. This can be explained by the very dilute Mg solute content in the Al solid solution, causing large spacing of Al–Mg lattice misfit sites and little impact on resistance of dislocation glide at initial yield. The 0.4 wt% Mg addition, on the other hand, has a large influence on the hardening term in the slip system parameters, indicating those Al–Mg misfit sites do help dislocation accumulation during the deformation. The impact of dilute Mg addition on the Al slip system parameters is also reflected in the flow behavior of the ternary alloy: little impact on the yield stress, but a large impact on working hardening and tensile strength of the materials which is consistent with the literature.

Image driven deep learning method with FFT solver for predicting the microscale full field stress of stochastic boundary composites

AbstractA novel image‐driven deep learning approach embedded with model‐data‐knowledge information can directly predict the full field stress distribution and mechanical properties of composites solely based on initial scanning geometry images. The fiber spatial distribution and morphological features are identified by Scanning Electron Microscopy (SEM) initially. An effective random fiber generation algorithm is further utilized to generate images database comprising equivalent geometric models of various microstructures. Subsequently, the geometry model images database is analyzed by fast Fourier transform (FFT) to produce the database including the elastic modulus parameters and full field stress distributions of composites with distinct microstructures. Finally, an innovative image‐learning comprehensive paradigm uniting convolutional neural networks and convolutional autoencoders is elaborated systematically to learn the inherent laws of geometry images and field images. The results show that the proposed method have capacity to effectively and accurately predict the elastic modulus and full field stress distributions combined with error analysis even for stochastic boundary composites. The proposed methodology is a symbiosis of cutting‐edge image learning and non‐destructive testing techniques for composites, which can directly use the local non‐destructive or scanning images of composite structural components to quickly obtain field information and further predict damage evolution online.Highlights Proposing a novel deep learning approach combined with FFT directly to predict stress distribution of stochastic boundary composites solely based on micro‐images. Adopting equivalent geometric models dispersed by higher pixels mesh density considering extreme thin interface. Incorporate adaptive algorithms for streamlined training optimization. An innovative integration of deep learning and non‐destructive testing technology for the stress distribution and properties prediction online.

Molecular insights into strengthening of biomineral apatite with carbon nanofillers: A simulation study

Biomineral apatite (Ap) has been widely utilized in clinical bone graft procedures for over 25 years. However, its lower tensile strength and fracture toughness compared to natural bone limit its application in large load-bearing systems. This approach aims to enhance the mechanical performance of Ap while preserving its bioactivity, thereby expanding its potential clinical applications. In this study, the creation and processing of carbon nanofiller-based Ap nanocomposites, including pristine and vacancy-defective carbon nanofillers, are investigated using molecular dynamics simulations. The mechanical behaviour of Ap nanocomposites reinforced with three types of carbon nanofillers (CNF) is examined: (i) three-dimensional metallic carbon nanostructure with interlocking hexagons T6B (beam-like), (ii) carbon nanotubes (CNT), and (iii) three-dimensional metallic carbon nanostructure with interlocking hexagons T6P (plate-like). The analysis encompasses detailing the methodology utilized for modelling the equilibrated structures of CNF/Ap nanocomposites, along with the characterization of their elastic parameters. Computational findings reveal the significant impact of CNT chirality, Aspect Ratio (AR) of T6B and orientation of T6P on the mechanical properties of the nanocomposites and observed inclusion of CNF enhances the mechanical properties compared with those of pure Ap. The findings indicate that the lower diameter CNT and smaller cross-sectional area of T6B exhibit higher tensile strength compared to the larger CNT diameter and larger cross-sectional area of T6B of the same length. Further, the analysis highlights the substantial influence of vacancy defects concentration on CNF on the mechanical behaviour of nanocomposites, with an increase in defects correlating to a decrease in the mechanical strength of both CNF and CNF-based nanocomposites.

CELASTO (Cervical ELASTOgraphy) pilot study — the use of cervical elastography during pregnancy

BACKGROUND: Ultrasound assessment of cervical length is an integral part of a comprehensive examination during pregnancy, but it does not provide a complete picture of structural changes in the cervix. The use of E-Cervix elastography is a promising method to assess cervical remodeling throughout the gestation period. AIM: The aim of this study was to evaluate the possibility of using automated cervical elastography in clinical practice to analyze the main parameters of cervical elasticity and hardness in pregnancy. MATERIALS AND METHODS: This prospective pilot study included 136 patients with singleton pregnancies at gestational ages ranging from 7+0 to 41+0 weeks. Cervical elastography was performed using E-Cervix software of the W10 diagnostic ultrasound system (Samsung Medison Co., Ltd., South Korea) with evaluation of quantitative parameters such as hardness ratio, elasticity contrast index, internal os, external os. RESULTS: Correlation analysis showed that hardness ratio decreased with increasing gestational age (ρ = −0.439) and decreasing cervical length (ρ = 0.408; p 0.001). In the group of patients with cervical length less than 25 mm, there was a decrease in hardness ratio compared to the control group (48.0 vs. 63.8%, respectively; p 0.001). The elasticity contrast index score, which reflects cervical tissue heterogeneity, increased with gestational age and cervical shortening (ρ = 0.368 and −0.450, respectively), the parameter being higher in patients with cervical length less than 25 mm [4.73 (IQR 4.21–5.90); p 0.001]. The increase in internal os and external os with gestational age (ρ = 0.433 and ρ = 0.365, respectively; p 0.001) indicates softening of the cervix and is accompanied by its shortening. CONCLUSIONS: Results indicate decreased hardness and increased elasticity of the cervix with increasing gestational age and decreased cervical length. E-Cervix technology allows for assessing structural changes in the cervix throughout pregnancy, starting from early gestation.

Newly synthesized Pb-based 312 MAX phases M3PbC2 (M = Zr and Hf): A First-principles study

The MAX phases' unique mixture of ceramic and metallic features makes them appealing for various technological uses. Zr3PbC2 and Hf3PbC2, two Pb-based MAX phases, were recently synthesized experimentally. The physical properties, such as structural properties as well as electronic, mechanical, hardness, thermal, and lastly, the optical properties of M3PbC2 (M = Zr and Hf) have been investigated using density functional theory (DFT) and analogized with those of other 312 MAX phases. The optimized cell volume and computed lattice constants match the experimental values. The calculated band structure certifies the metallic character, and DOS calculations confirmed the dominant contribution to conductivity from the Zr-4d and Hf-5d states. The stiffness constant (Cij) proved the mechanical stability of these compounds. The mechanical behavior of the studied compounds was explored by calculating the elastic moduli, hardness parameters, and fracture toughness, which are also compared to those of the 312 MAX phases. The tightly bound M–C covalent bonds within the crystal give these compounds high stiffness. The Mulliken population (both atomic and bond) was calculated to explore the bonding characteristics within them and the Vickers hardness of the titled phases. The degree of elastic anisotropy present within phases has been analyzed by calculating different indices. The phonon dispersion curves and phonon DOS (PHDOS) were computed to check the dynamical stability of the phases. Thermodynamic potential functions were calculated from the PHDOS. The thermal parameters were also studied, including the Debye temperature, melting temperature, Grüneisen parameter, and minimum thermal conductivity (Kmin). A thorough computation and analysis of the vital optical constants was done to explore their potential in diverse fields. The titled compounds are suitable for use as thermal barrier coating (TBC) materials and coating materials to prevent solar heating.

A novel dynamic stiffness matrix for the nonlocal vibration characteristics of porous functionally graded nanoplates on elastic foundation with small-scale effects

The present paper deals with the development of a dynamic stiffness matrix to evaluate the free vibration response of functionally graded nanoplate (FG-nP) resting on the Winkler-Pasternak elastic foundation. The complete mathematical modeling of the dynamic stiffness matrix for nanostructures is given for the first time. The equation of motion for rectangular FG-nP plates supported on an elastic foundation is derived using Hamilton’s principle in conjunction with nonlocal elasticity theory. The non-local theory is incorporated to account for the size effect in the small-scale plate. The effective material property of the porous FG-nP has been calculated using three recently developed models of porosity. The developed dynamic stiffness matrix is solved using the Wittrick-Williams algorithm to extract the natural frequencies of the FG-nP. The variation of natural frequencies with the change of numerical values, such as nonlocal parameter, aspect ratio, elastic foundation parameters, and porosity volume fraction is analyzed. The validity and accuracy of the results are confirmed through comparison with the available literature. The use of non-local theory in dynamic stiffness analysis is shown to be effective in predicting the natural frequency of the FG-nP on a Winkler-Pasternak elastic foundation, providing new insights into the dynamic behavior of small-scale structures.

In vivo mechanical response of thigh soft tissues under compression: A two-layer model allows an improved representation of the local tissue kinematics

Biomechanical parameters have the potential to be used as physical markers for prevention and diagnosis. Finite Element Analysis (FEA) is a widely used tool to evaluate these parameters in vivo. However, the development of clinically relevant FEA requires personalisation of the geometry, boundary conditions, and constitutive parameters. This contribution focuses on the characterisation of mechanical properties in vivo which remains a significant challenge for the community. The aim of this retrospective study is to evaluate the sensitivity of the computed elastic parameters (shear modulus of fat and muscle tissues) derived by inverse analysis as a function of the geometrical modelling assumption (homogenised monolayer vs bilayer) and the formulation of the cost function. The methodology presented here proposes to extract the experimental force-displacement response for each tissue layer (muscle and fat) and construct the associated Finite Element Model for each volunteer, based on data previously collected in our group (N = 7 volunteers) as reported in (Fougeron et al., 2020). The sensitivity analysis indicates that the choice of the cost function has minimal impact on the topology of the response surface in the parametric space. Each surface displays a valley of parameters that minimises the cost function. The constitutive properties of the thigh (reported as median ± interquartile range) were determined to be (μ=198±322Pa,α=37) for the monolayer and (μmuscle=1675±1127Pa,αmuscle=22±14,μfat=537±1131Pa,αfat=32±7) for the bilayer. A comparison of the homogenised monolayer and bilayer models showed that adding a layer reduces the error on the local force displacement curves, increasing the accuracy of the local kinematics of soft tissues during indentation. This allows for an increased understanding of load transmission in soft tissue. The comparison of the two models in terms of strains indicates that the modelling choice significantly influences the localization of maximal compressive strains. These results support the idea that the biomechanical community should conduct further work to develop reliable methodologies for estimating in vivo strain in soft tissue.

Parametric Optothermal Modulation of Carbon Nanooscillator Decorated with Mie Resonant Silicon Particle

AbstractNanomechanical resonators provide a versatile platform for nanoscale mass sensing and force microscopy, as well as for enhancing light‐matter interaction offering unique functionality for optomechanical applications. In this way, discovering new approaches for coupling light with the mechanical degrees of freedom opens the strong desire paths for further developing of nanomechanical technology. Here, the parametric optothermal modulation of hybrid nanomechanical systems consisting of carbon nanowire with a silicon nanoparticle on its top, is reported. The mechanism of the modulation is based on the periodic optical heating of the nanowire and further modulation of the elasticity parameters. Utilizing the silicon nanoparticle provides additional functionality owing to optical absorption enhanced with Mie resonance and the unique feature of optical Raman thermometry enabling optical monitoring of local temperature. It is shown that the parametric mechanism of modulation allows for a significant increase of the optomechanical coupling strength.

Utilizing wave propagation techniques to determine the influences of the type and size of coarse aggregates on the elastic properties of concrete

The results in the literature are not conclusive regarding the relationships between the strength of concrete and the particle size and type of coarse aggregates used in concrete production. Furthermore, few studies have used wave propagation to analyse these relationships. Therefore, this research used ultrasonic and static compression tests to evaluate the influences of these factors on the elastic parameters of 81 concrete test specimens produced with two maximum sizes of conventional coarse aggregates (9.5 mm and 12.5 mm) and lightweight aggregates (expanded clay). The ultrasonic testing results showed that the elastic parameters (longitudinal elastic modulus (E) and transverse elastic modulus (G)) were influenced by the type and size of the coarse aggregates; these influences were not detected in the static compression testing results. The results of the ultrasonic and static compression tests showed that the Poisson ratio was not influenced by the type or size of the coarse aggregates.

Forecasting optical response in lieu of electronic properties of TlCaF3 via halogen substitution for UV filtration: a DFT perspective

ABSTRACT It is demonstrated that the substitution of Cl, B, and I at different concentrations in TlCaF3 significantly alters the phase, electronic band structure and optical, elastic, mechanical and anisotropic properties of the material. At 2.81% and 5.63% concentrations of all substituted elements, the cubic phase of TlCaF3 transforms into a pseudo-cubic tetragonal phase. With the addition of substitutional atoms, a systematic considerable narrowing of the bandgap is seen, and it can be either direct or indirect depending on the symmetrical positions. The bandgap shrinking can be addressed, in part, via the total/partial/elemental density of states (DOS) in line with structural variations. From the optical response, the refractive index rises with substitution atoms. According to the mechanical stability requirements for each substitution, the determined elastic constants for cubic and tetragonal structures match. Additionally, using elastic parameters, it is possible to estimate the unique mechanical features to evaluate the ductility and brittleness of pure and substituted compounds. Furthernore, Cl, Br and I-atoms’ substitution would make them a suitable choice for improved optimisation in ultraviolet filters (UVF) due to the existence of their absorption spectra in the ultra-violet region and the modification in structural, electrical, optical, elastic and mechanical properties.