Hasil untuk "Mechanics of engineering. Applied mechanics"

A. Peirce

Patrick Diehl, R. Lipton, T. Wick et al.

Computational modeling of the initiation and propagation of complex fracture is central to the discipline of engineering fracture mechanics. This review focuses on two promising approaches: phase-field (PF) and peridynamic (PD) models applied to this class of problems. The basic concepts consisting of constitutive models, failure criteria, discretization schemes, and numerical analysis are briefly summarized for both models. Validation against experimental data is essential for all computational methods to demonstrate predictive accuracy. To that end, the Sandia Fracture Challenge and similar experimental data sets where both models could be benchmarked against are showcased. Emphasis is made to converge on common metrics for the evaluation of these two fracture modeling approaches. Both PD and PF models are assessed in terms of their computational effort and predictive capabilities, with their relative advantages and challenges are summarized.

Mohammed A. N Ali, Labed Kadhim Jawad, Ahmed Ibrahim Razooqi

This research studied experimentally the behavior of an aluminum alloy 7050 thin plate containing different sizes of circular central holes under thermo-mechanical fatigue crack growth testing. Transient thermal cyclic loading from 50℃ to 200℃ where applied, combined with constant tensile mechanical load at 200 kg at the edge of the plate. Three cases were experimentally tested based on the hole diameter of (1, 2, 3 mm) under the same testing conditions. Results show the increment of central hole diameter makes the crack initiation start earlier and crack growth increases then goes faster. Also, it has increased the stress intensity. The length of the second region of crack propagation related to stress intensity decreased when the hole size increased, and the slope changed too. For that, different Paris laws were obtained based on the central hole size. Accordingly, to these Paris laws, it can be easily informed and analyzed the behavior of any engineering structure made of this type of alloy under the same loading condition and predict its fracture or failure limits or lives.

Mohammed Saleh Alshaikh

The performance of Organic Solar Cells (OSCs) is intrinsically linked to the molecular, electronic, and structural properties of donor and acceptor materials. This study employs various machine learning techniques, namely the Generalized Regression Neural Network (GRNN), Support Vector Machine (SVM), and Tree Boost, to predict key performance metrics of OSCs, including power conversion efficiency (PCE), short-circuit current density (JSC), open-circuit voltage (VOC), and fill factor (FF). The models are trained and evaluated using an experimentally reported dataset compiled by Sahu et al. Correlation analysis demonstrates that material characteristics such as polarizability, bandgap, dipole moment, and charge transfer are statistically associated with OSC performance. The predictive performance of the GRNN model is compared with that of the SVM and Tree Boost models, showing consistently lower prediction errors within the considered dataset. In addition, sensitivity analysis is performed to assess the relative importance of the predictor variables and to examine the influence of kernel functions on GRNN performance. The results indicate that machine learning models, particularly GRNN, can serve as effective data-driven tools for predicting the performance of organic solar cells and for supporting computational screening studies.

Zehbah Ali Mohammed Al-Ahmed, Medhat M. Kamel, Mostafa A. A. Mahmoud et al.

Abstract The compound 4-amino-5-(trifluoromethyl)-4H-1,2,4-triazole-3-thiol (ATFS) was assessed for its effectiveness in preventing corrosion of low-carbon steel (LCS) in a hydrochloric acid (HCl) solution with a concentration of 0.5 mol L−1. The inhibition performance of the ATFS compound was investigated by chemical, electrochemical, and quantum studies. The surface morphology of LCS was studied by scanning electron (SEM) and atomic force (AFM) microscopes. At 298 K, the inhibitory efficiency (IE) increased from 52.27 to 89% as the inhibitor concentration increased from 50 to 300 ppm. However, at 328 K and with 300 ppm of the ATFS compound, the IE decreased to 74.51%. The Tafel plot confirmed that the ATFS compound belonged to mixed-type inhibitors. An increase in inhibitor’s concentration resulted in an elevation of the activation energy of the corrosion process, indicating that the ATFS was physically adsorbed at the LCS surface. The adsorption followed the Langmuir’s isotherm. The ATFS decreased the capacitance of the double layer (Cdl) and increased the charge transfer resistance (Rct). The AFM results indicated that the average roughness of LCS in the HCl solution was 7.58 nm, which reduced to 4.79 nm in the presence of 300 ppm of the ATFS compound. The high IE of the ATFS inhibitor was verified by the quantum parameters that derived from the density functional theory (DFT). The low hardness value of ATFS compound (η = 0.095) suggested its high adsorbability onto the steel surface, however, the high global softness (σ = 10.482) indicated its strong capability as an inhibitor. Monte Carlo (MC) simulations demonstrated that the adsorption energy of ATFS at the LCS surface is significantly negative (− 287.12 kJ mol−1), indicating a strong interaction between the AFTS and LCS.

Margaret Hawton

We second quantize the Fermi Lagrangian in the Lorenz gauge to obtain a covariant theory of photon quantum mechanics. Number density is real so it is interpreted as position probability density. The Hilbert space is the vector space of fields with norm 1 describing physical photons and the Poincare operators are extended to include position to represent observables. A photon continuity equation is derived that describes creation, propagation and annihilation of photons in an optical circuit. The relationship to orthodox quantum mechanics is discussed.

H. Geisler, P. Junker

A robust method for uncertainty quantification is undeniably leading to a greater certainty in simulation results and more sustainable designs. The inherent uncertainties of the world around us render everything stochastic, from material parameters, over geometries, up to forces. Consequently, the results of engineering simulations should reflect this randomness. Many methods have been developed for uncertainty quantification for linear elastic material behavior. However, real-life structure often exhibit inelastic material behavior such as visco-plasticity. Inelastic material behavior is described by additional internal variables with accompanying differential equations. This increases the complexity for the computation of stochastic quantities, e.g., expectation and standard deviation, drastically. The time-separated stochastic mechanics is a novel method for the uncertainty quantification of inelastic materials. It is based on a separation of all fields into a sum of products of time-dependent but deterministic and stochastic but time-independent terms. Only a low number of deterministic finite element simulations are then required to track the effect of (in)homogeneous material fluctuations on stress and internal variables. Despite the low computational effort the results are often indistinguishable from reference Monte Carlo simulations for a variety of boundary conditions and loading scenarios.

Soham Das, Soumya Kanti Biswas, Abhishek Kundu et al.

In this experimental investigation, a Physical Vapor Deposition (PVD) process was employed to deposit TiAlN coating onto a Si substrate. The nitrogen flow rate, bias voltage, and substrate-to-target distance were selected as input parameters, each with three different levels. The design of these input parameters was structured according to Taguchi's L9 Orthogonal Array (OA). Following deposition, the mechanical, microstructural, structural, and electrochemical properties of the TiAlN coating were meticulously characterized and analyzed to discern the influence of the selected parameters on its various properties. Microstructural analysis revealed a homogeneous structure throughout the film. Additionally, the mechanical properties of the film exhibited notable performance under the specified parameters. However, it was observed that no consistent trend could be identified across different properties concerning the applied parameters. To elucidate the complex relationships among these variables, the Least Squares Method (LSM) regression analysis technique was employed. This analytical approach facilitated the establishment of correlations among the diverse parameters, enhancing the understanding of their collective impact on the TiAlN coating properties. The understanding of analytical results will be useful for predicting the values between the two extremities to measure the performance parameters where the experimental results are not available.

Marcus Kessel, Colin Atkinson

The ability of Generative AI (GAI) technology to automatically check, synthesize and modify software engineering artifacts promises to revolutionize all aspects of software engineering. Using GAI for software engineering tasks is consequently one of the most rapidly expanding fields of software engineering research, with over a hundred LLM-based code models having been published since 2021. However, the overwhelming majority of existing code models share a major weakness - they are exclusively trained on the syntactic facet of software, significantly lowering their trustworthiness in tasks dependent on software semantics. To address this problem, a new class of "Morescient" GAI is needed that is "aware" of (i.e., trained on) both the semantic and static facets of software. This, in turn, will require a new generation of software observation platforms capable of generating large quantities of execution observations in a structured and readily analyzable way. In this paper, we present a vision and roadmap for how such "Morescient" GAI models can be engineered, evolved and disseminated according to the principles of open science.

Nazek A. Obeidat, M. Rawashdeh

In shallow waters, the Wu-Zhang (WZ) system describes the (1+1)-dimensional dispersive long wave in two horizontal directions, which is important for the engineering community. This paper presents proofs for various theorems and shows that the natural decomposition method (NDM) solves systems of linear and nonlinear ordinary and partial differential equations under proper initial conditions, such as the Wu-Zhang system. We use a combination of two methods, namely the natural transform method to deal with the linear terms and the Adomian decomposition method to deal with the nonlinear terms. Several examples of linear and nonlinear systems (ODEs and PDEs) are given, including the Wu-Zhang (WZ) system. The present approach, which has numerous applications in the science and engineering fields, is a great alternative to the many existing methods for solving systems of differential equations. It also holds great promise for additional real-world applications.

Syamsuir Syamsuir, Ferry Budhi Susetyo, Bambang Soegijono et al.

This study examines the influence of the application of a rotating magnetic field in the electrodeposition of copper (Cu). During the electrodeposition, five constant magnets were rotated (500 and 800 rpm) towards the bottom of the sample. To investigate deposition rate, surface morphology, phase, structure, corrosion resistance, and hardness in deposited Cu using a weighing scale, a scanning electron microscope equipped with energy dispersive spectroscopy (SEM-EDS), X-ray diffraction (XRD), potentiodynamic polarization, and hardness tester respectively. Bacterial activity was also evaluated through this research. Morphological surface observations showed that the increase in the rotational speed of the magnets during the electrodeposition process led to a smooth surface. A perfect Cu phase covers Al alloy with no oxide. The potentiodynamic polarization demonstrated by the increase in the rotating led to a shift to the more positive value of the corrosion potential. Moreover, the corrosion current also decreases with the increase in the rotating speed of the magnets. Less crystallite size promoted forming a higher hardness and inhibition zone of the Cu films.

Maciej Rogalka, Jakub Krzysztof Grabski, Tomasz Garbowski

The corrugated board is a versatile and durable material that is widely used in the packaging industry. Its unique structure provides strength and cushioning, while its recyclability and bio-degradability make it an environmentally friendly option. The strength of the corrugated board depends on many factors, including the type of individual papers on flat and corrugated layers, the geometry of the flute, temperature, humidity, etc. This paper presents a new approach to the analysis of the geometric features of corrugated boards. The experimental set used in the work and the created software are characterized by high reliability and precision of measurement thanks to the use of an identification procedure based on image analysis and a genetic algorithm. In the applied procedure, the thickness of each layer, corrugated cardboard thickness, flute height and center line are calculated. In most cases, the proposed algorithm successfully approximated these parameters.

Andrey V. Kuznetsov

The aim of this paper is to establish the bounds of applicability of the single-domain numerical approach for computations of convection in composite porous/ fluid domains. The large number of papers that have utilized this numerical approach motivates this research. The popularity of this approach is due to the simplicity of its numerical formulation. Since the utilization of the single-domain numerical approach does not require the explicit imposing of any boundary conditions at the porous/ fluid interface, the aim of the this research is to investigate whether this method always produces accurate numerical solutions.

Huy T. Q. Phan, Duc M. Bui, Cong T. Than et al.

Fractals are ubiquitous natural emergences that have gained increased attention in engineering applications, thanks to recent technological advancements enabling the fabrication of structures spanning across many spatial scales. We show how the geometries of fractals can be exploited to determine their important mechanical properties, such as the first and second moments, which physically correspond to the center of mass and the moment of inertia, using a family of complex fractals known as the dragons.

P. E. Brandyshev, Yu. A. Budkov

In this paper, we introduce a statistical field theory that describes the macroscopic mechanical forces in inhomogeneous Coulomb fluids. Our approach employs the generalization of Noether's first theorem for the case of fluctuating order parameter, to calculate the stress tensor for Coulomb fluids. This tensor encompasses the mean-field stress tensor and the fluctuation corrections derived through the one-loop approximation. The correction for fluctuations includes a term that accounts for the thermal fluctuations of the local electrostatic potential and field in the vicinity of the mean-field configuration. This correlation stress tensor determines how electrostatic correlation affects local stresses in a nonuniform Coulomb fluid. We also use previously formulated general covariant methodology [P.E. Brandyshev and Yu.A. Budkov, J. Chem. Phys. 158, 174114 (2023)] in conjunction with a functional Legendre transformation method and derive within it the same total stress tensor. We would like to emphasize that our general approaches are applicable not only to Coulomb fluids but also to nonionic simple or complex fluids, for which the field-theoretic Hamiltonian is known as a functional of the relevant scalar order parameters.

Kenric P. Nelson

Nonextensive Statistical Mechanics has developed into an important framework for modeling the thermodynamics of complex systems and the information of complex signals. Upon the 80th birthday of the field's founder, Constantino Tsallis, a review of open problems that can stimulate future research is provided. Over the thirty-year development of NSM a variety of criticisms have been published ranging from questions about the justification for generalizing the entropy function to interpretation of the generalizing parameter q. While these criticisms have been addressed in the past and the breadth of applications has demonstrated the utility of the NSM methodologies, this review provides insights on how the field can continue to improve the understanding and application of complex system models. The review starts by grounding q-statistics within scale-shape distributions and then frames a series of open problems for investigation. The open problems include using the degree of freedom to quantify the difference between entropy and its generalization; clarifying the physical interpretation of the parameter q; improving the definition of the generalized product using multidimensional analysis; defining a generalized Fourier transform applicable to signal processing applications; and re-examination of the normalization of nonextensive entropy. The review concludes with a proposal that the shape parameter is a candidate for defining the statistical complexity of a system.

Shu-yang Yu, X. Ren, Ji-xun Zhang et al.

Abstract The simulation of crack propagation processes in rock engineering has been not only a research hot spot among scholars but also a challenge. Based on this background, a new numerical method named improved kernel of smoothed particle hydrodynamics (IKSPH) has been put forward. By improving the kernel function in the traditional smoothed particle hydrodynamics (SPH) method, the brittle fracture characteristics of the base particles are realized. The particle domain searching method (PDSM) has also been put forward to generate the arbitrary complex fissure networks. Three numerical examples are analyzed to validate the efficiency of IKSPH and PDSM, which can correctly reveal the morphology of wing crack and the laws of crack coalescence compared with previous experimental and numerical studies. Finally, a rock slope model with complex joints is numerically simulated and the progressive failure processes are exhibited, which indicates that the IKSPH method can be well applied to rock mechanics engineering. The research results showed that IKSPH method reduces the programming difficulties and avoids the traditional grid distortion, which can provide some references for the application of IKSPH to rock mechanics engineering and the understanding of rock fracture mechanisms.

S. Faghidian

Two frameworks of the nonlocal integral elasticity and the modified strain gradient theory are consistently merged to conceive the nonlocal modified gradient theory. The established augmented continuum theory is applied to a Timoshenko–Ehrenfest beam model. Nanoscopic effects of the dilatation, the deviatoric stretch, and the symmetric rotation gradients together with the nonlocality are suitably accommodated. The integral convolutions of the constitutive law are restored with the equivalent differential model subject to the nonclassical boundary conditions. Both the elastostatic and elastodynamic flexural responses of the nano-sized beam are rigorously investigated and the well posedness of the nonlocal modified gradient problems on bounded structural domains is confirmed. The analytical solution of the phase velocity of flexural waves and the deflection and the rotation fields of the nano-beam is detected and numerically illustrated. The transverse wave propagation in carbon nanotubes is furthermore reconstructed and validated by the molecular dynamics simulation data. Being accomplished in revealing both the stiffening and softening structural responses at nano-scale, the proposed nonlocal modified gradient theory can be beneficially implemented for nanoscopic examination of the static and dynamic behaviors of stubby nano-sized elastic beams.

Chang Jiahui, Dongjia Yan, Jianxing Liu et al.

Inspired by the helix-shaped microstructures found in many collagenous tissues, a class of three-dimensional (3D) soft network materials that incorporate similar helical microstructures into periodic 3D lattices was reported recently. Owing to their high stretchability, high air permeability, defect-insensitive behavior and capabilities of reproducing anisotropic J-shaped stress-strain curves of real biological tissues (e.g., heart muscles), these 3D soft network materials hold great promise for applications in tissue engineering and bio-integrated devices. Rapid design optimization of such soft network materials in practical applications requires a relevant mechanics model to serve as the theoretical basis. This paper introduces a nonlinear micromechanics model of soft 3D network materials with cubic and octahedral lattice topologies, grounded on the development of finite-deformation beam theory for the 3D helical microstructure (i.e., the building-block structure of 3D network materials). As verified by finite element analysis (FEA) and experimental measurements, the developed model can well predict the anisotropic J-shaped stress-strain curves and deformed configurations under large levels of uniaxial stretching. The theoretical model allows a clear understanding of different roles of microstructure parameters on the J-shaped stress-strain curve (that is characterized by the critical strain of mode transition, as well as the stress and the tangent modulus at the critical strain). Furthermore, we demonstrate the utility of the theoretical model in the design optimization of 3D soft network materials to reproduce the target isotropic/anisotropic stress-strain curves of real biological tissues.