Hasil untuk "Mechanics of engineering. Applied mechanics"

Luigi Piccinini, Luca Emanuele Molteni, Daniele Panzeri et al.

<b>Background:</b> Gait assessment is a complex task involving locomotion and balance control across all body segments, requiring a global analysis in the event of motor disorders. Among these are spinal disorders, where an understanding of spinal kinematics during walking is important to improve treatment decisions and outcomes. The technique of stereophotogrammetric motion analysis is currently the gold standard in this context. A new integrated protocol for whole-body kinematic gait analysis is proposed in this study, which takes into account the movements of the spine. <b>Methods:</b> A new protocol with 30 passive markers was developed to analyze gait. Of these markers, 22 implemented the Davis protocol for gait measurement, while the other 8 were placed onto the spine to record spinal movements. The protocol’s accuracy was assessed through comparisons of the constructive angles of a manikin replicating the human body and the angles measured with the optoelectronic system. An assessment of intra- and inter-operator repeatability and protocol usability was carried out by recruiting and applying the protocol in a population composed of ten subjects (mean age 17.36—SD 10.12) without any history of spine pathology. <b>Results:</b> The protocol was validated successfully. The validation accuracy was more than satisfactory: the measured RMSE was 1.2 ± 1° for the data collected with the optoelectronic system with respect to the manikin. The intra-operator repeatability was also good in the sagittal and frontal planes (average ICC > 0.867), and the inter-operator repeatability was moderate or good in all planes (average ICC > 0.77). The usability score obtained using the System Usability Scale was satisfactory (mean 74.75, SD 5.88). <b>Conclusions:</b> This study proposes a new protocol to assess total body kinematics, including the spine in its three main segments, during gait. The successful validation of this protocol in terms of reliability and usability allows for its subsequent clinical application.

Chandra Pasapula, Nicolas Yanguma, Brayan David Solorzano et al.

<b>Introduction:</b> Management strategies for stage II tibialis posterior tendon dysfunction are centered on tendon transfers and osteotomies. One of the most commonly used tendon transfers is flexor digitorum longus (FDL) tendon to navicular, but its superiority over transfers to other locations or transfers of other tendons, along with the role of spring ligament and tibialis posterior tendons, have not been objectively evaluated. <b>Aims:</b> We aimed to quantify both the location and magnitude of secondary stresses that develop as a consequence of the initial pathology. <b>Methods:</b> In this study, we used a computational model to study flat foot development and evaluate the effects of various tendon transfers and failures of passive structural elements, as well as their effect on the biomechanics of the foot. <b>Results:</b> We found that both FDL and FHL transfers have biomechanical advantages and disadvantages. Neither of these transfers decrease the stress on the tibialis posterior tendon if the underlying pathologies such as spring ligament failure are not addressed. <b>Conclusions:</b> Of the tendon transfers evaluated, FDL transfer to the navicular had the most profound effect on reducing the stresses on the spring ligament.

Lekshmi Murali Rani

The study of behavioral and social dimensions of software engineering (SE) tasks characterizes behavioral software engineering (BSE);however, the increasing significance of human-AI collaboration (HAIC) brings new directions in BSE by presenting new challenges and opportunities. This PhD research focuses on decision-making (DM) for SE tasks and collaboration within human-AI teams, aiming to promote responsible software engineering through a cognitive partnership between humans and AI. The goal of the research is to identify the challenges and nuances in HAIC from a cognitive perspective, design and optimize collaboration/partnership (human-AI team) that enhance collective intelligence and promote better, responsible DM in SE through human-centered approaches. The research addresses HAIC and its impact on individual, team, and organizational level aspects of BSE.

José F. Cariñena, Jesús Clemente-Gallardo, Giuseppe Marmo

The conditions under which a given manifold $M$ may be given a tangent bundle or a cotangent bundle structure are analyzed. This is an important property arising in different contexts. For instance, in the study of integrability of a given dynamics the existence of alternative compatible structures is very relevant, as well as in the geometric approach to Classical Mechanics. On the other hand in the quantum-to-classical transition, a Weyl system plays an important role for it provides (within the so-called Weyl-Wigner formalism) a description of quantum mechanics on a (symplectic) phase-space $M$. A Lagrangian subspace $Q\subset M$ of the (linear) phase space determines thus a maximal set of pairwise commuting unitary operators, which is used to parametrize the quantum states. As the choice of this maximal Abelian set of observables is not unique, the different choices make the phase space to become diffeomorphic to different cotangent bundles $T^*Q$ corresponding to different choices for the base manifold (and hence the fibers). These motivating ideas are used to study how to define alternative tangent and/or cotangent bundle structures on a phase space.

Max Neuwinger, Dirk Riehle

The design of effective programming languages, libraries, frameworks, tools, and platforms for data engineering strongly depends on their ease and correctness of use. Anyone who ignores that it is humans who use these tools risks building tools that are useless, or worse, harmful. To ensure our data engineering tools are based on solid foundations, we performed a systematic review of common programming mistakes in data engineering. We focus on programming beginners (students) by analyzing both the limited literature specific to data engineering mistakes and general programming mistakes in languages commonly used in data engineering (Python, SQL, Java). Through analysis of 21 publications spanning from 2003 to 2024, we synthesized these complementary sources into a comprehensive classification that captures both general programming challenges and domain-specific data engineering mistakes. This classification provides an empirical foundation for future tool development and educational strategies. We believe our systematic categorization will help researchers, practitioners, and educators better understand and address the challenges faced by novice data engineers.

Fatima M. Hassan, Waad A. Zakraia

A retaining wall was practically developed to provide lateral support for soil, and it is widely used in underground projects, highway barriers, and mines as well as for aesthetic considerations and slope stabilization. This type of earth structure member can carry machine foundation load simultaneously with traditional static load. This study carried out using the finite element program PLAXIS 3D. The linear elastic model for retaining walls and the Mohr-Coulomb model for soil layers were used in this numerical analysis. The study included three layers of soils under the wall with dry condition. The high of the wall was 4m and the dimensions of machine foundation were 3x3m. It can be concluded that the vertical settlement, horizontal displacement and velocity increased when the duration of the machine load increases. Usually, the horizontal displacement increases to highest value and reached to 10 times the original static value when the machine was closed to the wall with 0.5m and 75Hz. This can be taken into account in the design for such geotechnical system in the design stages.

Salma Jahan, Rehena Nasrin

Abstract Microchannel heat exchangers have become the preferred choice in contemporary technologies like electronics, refrigeration, and thermal management systems. Their popularity stems from their compact design and exceptional efficiency, which outperform traditional heat exchangers (HE). Despite ongoing efforts, the optimal microchannels for enhancing heat management, minimizing pressure drop, and boosting overall performance have yet to be identified. This study seeks to deepen our understanding of heat transmission and fluid dynamics within a cross-flow microchannel heat exchanger (CFMCHE). Utilizing numerical modeling, it examines how various physical aspects—such as channel geometry, spacing between channels, the number of channels, and the velocity at the inlet—affect key performance indicators like pressure drop, effectiveness, Nusselt number, and overall efficiency. To enhance the design, we analyze six unique shapes of crossflow microchannel heat exchangers: circular, hexagonal, trapezoidal, square, triangular, and rectangular. We employ the Galerkin-developed weighted residual finite element method to numerically address the governing three-dimensional conjugate partial differential coupled equations. The numerical results for each shape are presented, focusing on the surface temperature, pressure drop, and temperature contours. Additionally, calculations include the efficacy, the heat transfer rate in relation to pumping power, and the overall performance index. The findings reveal that while circular shapes achieve the highest heat transfer rates, they underperform compared to square-shaped CFMCHEs. This underperformance is largely due to the increased pressure drop in circular channels, which also exhibit a 1.03% greater reduction in effectiveness rate than their square-shaped counterparts. Consequently, square-shaped channels, boasting a performance index growth rate of 53.57%, emerge as the most effective design among the six shapes evaluated. Additionally, for the square-shaped CFMCHE, we include residual error plots and present a multiple-variable linear regression equation that boasts a correlation coefficient of 0.8026.

Jun Tsuzurugi

In this paper, we analyze Gaussian processes using statistical mechanics. Although the input is originally multidimensional, we simplify our model by considering the input as one-dimensional for statistical mechanical analysis. Furthermore, we employ periodic boundary conditions as an additional modeling approach. By using periodic boundary conditions, we can diagonalize the covariance matrix. The diagonalized covariance matrix is then applied to Gaussian processes. This allows for a statistical mechanical analysis of Gaussian processes using the derived diagonalized matrix. We indicate that the analytical solutions obtained in this method closely match the results from simulations.

Marco Baldovin, Giacomo Gradenigo, Angelo Vulpiani et al.

Although not as wide, and popular, as that of quantum mechanics, the investigation of fundamental aspects of statistical mechanics constitutes an important research field in the building of modern physics. Besides the interest for itself, both for physicists and philosophers, and the obvious pedagogical motivations, there is a further, compelling reason for a thorough understanding of the subject. The fast development of models and methods at the edge of the established domain of the field requires indeed a deep reflection on the essential aspects of the theory, which are at the basis of its success. These elements should never be disregarded when trying to expand the domain of statistical mechanics to systems with novel, little known features. It is thus important to (re)consider in a careful way the main ingredients involved in the foundations of statistical mechanics. Among those, a primary role is covered by the dynamical aspects (e.g. presence of chaos), the emergence of collective features for large systems, and the use of probability in the building of a consistent statistical description of physical systems. With this goal in mind, in the present review we aim at providing a consistent picture of the state of the art of the subject, both in the classical and in the quantum realm. In particular, we will highlight the similarities of the key technical and conceptual steps with emphasis on the relevance of the many degrees of freedom, to justify the use of statistical ensembles in the two domains.

Johanna Müller, Florian Sammüller, Matthias Schmidt

We give an introductory account of the recently identified gauge invariance of the equilibrium statistical mechanics of classical many-body systems [J. Müller et al., Phys. Rev. Lett. Phys. Rev. Lett. 133, 217101 (2024)]. The gauge transformation is a non-commutative shifting operation on phase space that keeps the differential phase space volume element and hence the Gibbs integration measure conserved. When thermally averaged any observable is an invariant, including thermodynamic and structural quantities. Shifting transformations are canonical in the sense of classical mechanics. They also form an infinite-dimensional group with generators of infinitesimal transformations that build a non-commutative Lie algebra. We lay out the connections with the underlying geometry of coordinate displacement and with Noether's theorem. Spatial localization of the shifting yields differential operators that satisfy commutator relationships, which we describe both in purely configurational and in full phase space setups. Standard operator calculus yields corresponding equilibrium hyperforce correlation sum rules for general observables and order parameters. Using Monte Carlos simulations we demonstrate explicitly the gauge invariance for finite shifting. We argue in favour of using the gauge invariance as a statistical mechanical construction principle for obtaining exact results and for formulating smart sampling algorithms.

Jindřich Hodač, Kateřina Kovářová, Michal Cihla et al.

Traces of stone working are an integral part of natural stone objects and artefacts of historical value. Each preserved trace does not only carry a value in determining the type of tool used, but also provides information about the historic stonemason’s work process and technology. For this reason, it is desirable to assess the restoration method’s influence on the change in surface topography. The effect of restoration interventions was investigated on five stone artefacts, three of ‘opuka’, one of sandstone and one of limestone, four of which showed historic working traces. For this purpose, selected restoration methods—chemical, mechanical and laser—were used. The examined artefacts were accurately photogrammetrically captured before and after the restoration interventions in order to assess and evaluate changes in the degree of preservation of the traces. Fine results using common tools were achieved in terms of geometric quality, level of detail and the documentation’s predictive power. The models’ geometric accuracy is in the single tenths of mm, as well as the matching of the two datasets (before and after).

Libor Ižvolt, Peter Dobeš, Daniel Papán et al.

The paper focuses on the analysis of the values of the static modulus of deformation obtained by the application of the test procedure specified in the methodology for the diagnostics of the sub-ballast layers used for German railways (DIN 18 134) and the Railways of the Slovak Republic (Regulation TS4). The purpose of the study was to determine the correlation between the measured values of the static modulus of deformation according to the above-mentioned methodologies based on a series of experimental measurements on an experimental field built at a scale of 1:1. It also aimed to develop a numerical model characterising the behaviour of the loaded environment during the experimental measurements using the finite element method, which can subsequently be used for the design of the structural composition of the sub-ballast layers. For the purpose of the experimental measurements, a sub-ballast layer of 0/31.5 mm crushed aggregate of different design thicknesses was applied to the sub-ballast layers. A polynomial dependence with a high value of the reliability coefficient can be found between the results of the static modulus of deformation obtained using the mentioned measurement methodologies during the quality inspection of the implemented construction works. This dependence is valid for the specific boundary conditions of the experimental measurements performed (subsoil of clay with gravel admixture and the sub-ballast crushed aggregate layer of 0/31.5 mm dolomitic gravel). In the future, establishing correlation dependencies for other boundary conditions and structural material compositions can be considered.

Alberto Gaxiola, Alexandra Ossa, Laura González-Maturana et al.

Recently, high aspect ratio materials like nanofibers with outstanding mechanical properties have been developed and used to improve the mechanical characteristics of construction materials. However, despite the excellent results obtained in asphalt binder modification, only a few types of polymeric nanofibers have been used for this purpose. In this sense, polyacrylonitrile has good thermal and mechanical characteristics to maintain the shape at the typical temperatures the asphalt is heated.This study evaluates the effect of electrospun polyacrylonitrile (PAN) nanofibers on the rutting resistance and fatigue parameters of asphalt binders. For this, fibers with an average diameter of 1.3 µm were prepared and randomly dispersed into neat PG 64–22 asphalt binder. Subsequently, a dynamic shear rheometer (DSR) was used to determine G*/sin δ, Jnr, R3.2, and Nf.In the range studied, Jnr3.2 showed a reduction of up to 35%, and the elastic recovery increased up to 4.5 times compared to the reference material. It was observed that the PAN nanofibers increased the fatigue resistance of asphalt binder at temperatures when the material is predominantly viscoelastic. These results show a promising new application of PAN nanofibers to improve the performance of asphalt pavements.

Haoyan Wei, C. T. Wu, Wei Hu et al.

Short-fiber-reinforced composites (SFRC) are high-performance engineering materials for lightweight structural applications in the automotive and electronics industries. Typically, SFRC structures are manufactured by injection molding, which induces heterogeneous microstructures, and the resulting nonlinear anisotropic behaviors are challenging to predict by conventional micromechanical analyses. In this work, we present a machine learning-based multiscale method by integrating injection molding-induced microstructures, material homogenization, and Deep Material Network (DMN) in the finite element simulation software LS-DYNA for structural analysis of SFRC. DMN is a physics-embedded machine learning model that learns the microscale material morphologies hidden in representative volume elements of composites through offline training. By coupling DMN with finite elements, we have developed a highly accurate and efficient data-driven approach, which predicts nonlinear behaviors of composite materials and structures at a computational speed orders-of-magnitude faster than the high-fidelity direct numerical simulation. To model industrial-scale SFRC products, transfer learning is utilized to generate a unified DMN database, which effectively captures the effects of injection molding-induced fiber orientations and volume fractions on the overall composite properties. Numerical examples are presented to demonstrate the promising performance of this LS-DYNA machine learning-based multiscale method for SFRC modeling.

D. Proserpio, J. Kiendl

We present a formulation for isogeometric Kirchhoff–Love shell analysis on complex CAD models consisting of multiple trimmed patches. The method is based on the penalty coupling method presented in Herrema AJ, Johnson EL, Proserpio D, Wu MCH, Kiendl J, Hsu MC (Penalty coupling of non-matching isogeometric Kirchhoff–Love shell patches with application to composite wind turbine blades. Computer Methods in Applied Mechanics and Engineering 2019;346:810–840.) and extended to the application on arbitrary coupling curves defined either in the physical or parametric space. We present the detailed formulation ready for implementation. Different numerical tests demonstrate the accuracy and applicability of the method.

Володимир Семененко, Володимир Мороз, Віктор Кочін et al.

The work is devoted to theoretical and experimental investigations of dynamics of high-speed underwater supercavitating vehicles with cone cavitators. The cone cavitators are considered as operating controls of the supercavitating vehicle motion. The mathematical model of a “slender” unsteady cavity based on the G.V.Logvinovich principle of independence of the cavity section expansion is used. Experimental studies of the rotary cone cavitators were carried out at the high-speed experimental tank of the Institute of Hydromechanics of the NAS of Ukraine. Based on test results, the approximate dependences of both the drag coefficient and the lift coefficient of an inclined cone cavitator on the rotary angle in a wide range of cone angles are proposed. The range of cone angles is determined when the cone cavitators are the more effective operating controls in comparison with equivalent disk cavitator. With the help of computer simulation, a number of problems of dynamics of the supercavitating vehicle with cone cavitators were investigated: balancing the vehicle, the motion stabilization, maneuvering the vehicle, the cavity control. For the first time, experimental verification of the mathematical model of the supercavitating vehicle dynamics “as a whole” was performed by testing the model with cone cavitators and cavity-piercing fins with a degree of freedom in pitch.

Ali Saberi Varzaneh, Mahmood Naderi

The separation between repair mortars and the concrete substrate is one of the serious problems in repairing concrete structures. One of the main causes of this separation is the lack of proper curing and, consequently, excessive shrinkage of the repair mortar, which reduces the bond strength between the concrete substrate and the repair layer and has an adverse effect on the compressive and tensile strength of the repair mortars. In this paper, the mechanical properties, shrinkage of repair mortars, as well as their shear and tensile bond strength is investigated on the concrete substrate of different ages under the curings of "abandoned in the laboratory space," "water-submerged" and "curing agent." In-situ "friction-transfer" and "pull-off" methods are used to measure adhesion. Furthermore, the relationships between compressive strength, tensile strength, and readings are obtained from "friction-transfer" and "pull-off" methods on repair mortars and the stress distribution method used in the above-mentioned methods are presented using nonlinear finite element analysis (Abaqus/CAE). The results indicate a significant effect of curing method on shrinkage and mechanical properties of repair mortars; as a result, effective curing increases the shear and tensile bond strength at the substrate and repair layer joint boundary. It is also observed that there is a linear relationship between the experimental results obtained from the two methods used in this study with a high correlation coefficient, highly consistent with the results obtained from nonlinear finite element analysis. Thus, they can be used as in-situ methods for determining the compressive and tensile strength of repair mortars.

CHRISTOPHER JANTING LIEW CHALU

Mathematical modelling was developed for direct ethanol fuel cell (DEFC) by considering electrochemical reactions and mass transport. The model was validated against experimental data from previous research and showed good agreement with the data. The developed mathematical modelling for this research was based on the Butler-Volmer equation, Tafel equation and Fick’s law. The model was used to investigate parameters such as ethanol concentration and cell operating temperature. The developed mathematical model simulated the data from previous research. Ethanol concentration played a vital role to achieve high-performance DEFC. The higher the ethanol concentration, the higher current could be generated in DEFC. Nonetheless, the higher the usage of the ethanol concentration, the higher the ethanol crossover might occur. The highest current density produced from the fuel cell was at 21.48 mA cm-2, for 2M of ethanol concentration. Operating temperature also affected cell performance. The higher the operating temperature, the higher power density could be generated—the peak power density of 5.7 mWcm-2 at 75 oC with 2M of ethanol. As for ethanol crossover, the highest ethanol crossover was at 12.4 mol m-3 for 3M concentration of ethanol. It proved that higher ethanol concentration led to higher ethanol crossover.

Panos Pantidis, Mostafa E. Mobasher

We present a new Integrated Finite Element Neural Network framework (I-FENN), with the objective to accelerate the numerical solution of nonlinear computational mechanics problems. We leverage the swift predictive capability of neural networks (NNs) and we embed them inside the finite element stiffness function, to compute element-level state variables and their derivatives within a nonlinear, iterative numerical solution. This process is conducted jointly with conventional finite element methods that involve shape functions: the NN receives input data that resembles the material point deformation and its output is used to construct element-level field variables such as the element Jacobian matrix and residual vector. Here we introduce I-FENN to the continuum damage analysis of quasi-brittle materials, and we establish a new non-local gradient-based damage framework which operates at the cost of a local damage approach. First, we develop a physics informed neural network (PINN) to resemble the non-local gradient model and then we train the neural network offline. The network learns to predict the non-local equivalent strain at each material point, as well as its derivative with respect to the local strain. Then, the PINN is integrated in the element stiffness definition and conducts the local to non-local strain transformation, whereas the two PINN outputs are used to construct the element Jacobian matrix and residual vector. This process is carried out within the nonlinear solver, until numerical convergence is achieved. The resulting method bears the computational cost of the conventional local damage approach, but ensures mesh-independent results and a diffused non-local strain and damage profile. As a result, the proposed method tackles the vital drawbacks of both the local and non-local gradient method, respectively being the mesh-dependence and additional computational cost.