Theoretical Modeling Research Articles

Analysis of Bolt Loosening due to Transvers Vibration

Bolt loosening is a critical issue in engineering applications where vibration-induced failures pose significant risks to the structural integrity and functionality of mechanical systems. This project aims to investigate the phenomenon of bolt loosening resulting from the transfer of vibrations and develop effective strategies to mitigate this problem. The study employs a comprehensive approach, combining experimental analysis, numerical simulations, and theoretical modeling to gain insights into the underlying mechanisms of bolt loosening. Furthermore, a theoretical model is developed to predict the susceptibility of different bolted joints to loosening based on factors such as material properties, bolt size, and tightening torque. The model is validated using experimental data, ensuring its accuracy and reliability in practical applications.

A plate containing a central rectangular hole made of PMMA resin and reinforced with graphene particles: low-velocity impact analysis

Purpose Due to the important and extensive use of graphene in the engineering structures, the purpose of this paper is to investigate the low-velocity impact (LVI) response of a graphene-reinforced plate with a rectangular central hole. Design/methodology/approach In this paper, Halpin-Tsai theory is used to model the mechanical properties of the plate made of polymethyl methacrylate (PMMA) resin and graphene particles. First, the plate displacement field is presented, and then the strains and stresses are obtained. The motion equations are extracted using energy equations, Ritz method and generalized Lagrange equations. The verification of theoretical formulation shall be carried out using the ABAQUS finite element software suite. Findings The effects of graphene volume fraction, approaching the impact point to the corner of the rectangular plate, and different boundary conditions of the plate are studied for LVI of impactor with spherical tip on the rectangular central hole reinforced by graphene. Important responses of the impact, such as the contact force between the impactor and the plate as well as the displacement of the plate at the impact place, are investigated and analyzed in this research. Originality/value Considering the wide application of graphene in the engineering structures, the simulation of the LVI on the graphene-reinforced plate made of PMMA resin with a rectangular central hole is carried out in this paper using numerical and theoretical modeling.

Cascade-Dissipation Balance in Astrophysical Plasmas: Insights from the Terrestrial Magnetosheath.

The differential heating of electrons and ions by turbulence in weakly collisional magnetized plasmas and the scales at which such energy dissipation is most effective are still debated. Using a large data sample measured in Earth's magnetosheath by the magnetospheric multiscale mission and the coarse-grained energy equations derived from the Vlasov-Maxwell system, we find evidence of a balance over two decades in scales between the energy cascade and dissipation rates. The decline of the cascade rate at kinetic scales (in contrast with a constant one in the inertial range), is balanced by an increasing ion and electron heating rates, estimated via the pressure strain. Ion scales are found to contribute most effectively to ion heating, while electron heating originates from both ion and electron scales. These results can potentially impact the current understanding of particle heating in turbulent magnetized plasmas as well as their theoretical and numerical modeling.

Highly confined epsilon-near-zero and surface phonon polaritons in SrTiO3 membranes

Recent theoretical studies have suggested that transition metal perovskite oxide membranes can enable surface phonon polaritons in the infrared range with low loss and much stronger subwavelength confinement than bulk crystals. Such modes, however, have not been experimentally observed so far. Here, using a combination of far-field Fourier-transform infrared (FTIR) spectroscopy and near-field synchrotron infrared nanospectroscopy (SINS) imaging, we study the phonon polaritons in a 100 nm thick freestanding crystalline membrane of SrTiO3 transferred on metallic and dielectric substrates. We observe a symmetric-antisymmetric mode splitting giving rise to epsilon-near-zero and Berreman modes as well as highly confined (by a factor of 10) propagating phonon polaritons, both of which result from the deep-subwavelength thickness of the membranes. Theoretical modeling based on the analytical finite-dipole model and numerical finite-difference methods fully corroborate the experimental results. Our work reveals the potential of oxide membranes as a promising platform for infrared photonics and polaritonics.

Power Components Mean Values Determination Using New Ip-Iq Method for Transients

This paper deals with the quasi-instantaneous determination (in a single-step response time) of apparent, active, and reactive (i.e., blind and distortion) power mean values including the total power factor, total harmonic distortion, and phase shift of fundamentals of a power electronic and electrical system (PEES) using the ip-iq method, which is the main contribution of the paper. The power components’ mean values are investigated during the transient and steady states. The power components’ mean values can be determined directly from phase current and voltage quantities, using an integral calculus over one period within the next calculation step and using moving average and moving rms techniques (or digital filtering). Consequently, the power factor can be evaluated with known values of a phase shift of fundamentals (using a Fourier analysis). The results of this study show how a distortion power component during transients is generated even under a harmonic supply and linear resistive–inductive load. The paper contains a theoretical base, modeling, and simulation for the three and single phases of the transients in power electronic systems. The worked-out results can be used to determine and size any PES. The presented approach brings a detailed time waveform verified by simulations in Matlab/Simulink 2022a and the Real-time HW Simulator Plecs RT Box 1.

Nuclear quantum effects in phase transition between Ice VII and Ice X.

The theoretical modeling of high-pressure ice remains challenging owing to the complexity in accurately reflecting its properties attributable to nuclear quantum effects. To explore the nuclear quantum effects of the phase transition between Ice VII and Ice X, we introduce an approach based on abinitio path-integral molecular dynamics. The results indicate that quantum effects facilitate the phase transition, with the observed isotope effects consistent with the experimental outcomes. We demonstrate that quantum effects manifest differently across ice phases: In Ice VII, quantum effects reduce the pressure through the centralization of protons. In contrast, in Ice X, quantum effects increase the pressure owing to the increased kinetic energy of zero-point vibration.

Studying high-energy nuclear physics with machine learning

The research paradigm in physics has evolved through three distinct phases: empirical observation and induction, theoretical modeling and deduction and computational numerical analysis and simulation. We are now situated within a novel epoch wherein the scientific research paradigm is increasingly shaped by the preeminence of large-scale data and artificial intelligence, particularly within the realm of AI for science applications. The advent of high-energy colliders coupled with Monte Carlo simulations has given rise to an unprecedented accumulation of data. Nested within this transformative research paradigm, machine learning and artificial intelligence technologies have been extensively harnessed for the analysis of these vast data sets. Within the domain of high-energy nuclear physics, two prevalent machine learning techniques have emerged: Bayesian analysis and deep learning. The former employs comprehensive fitting methodologies that compare extensive data sets against theoretical models, enabling the extraction of critical information pertaining to the initial nuclear structure, parton distributions, the equation of state governing hot and dense nuclear matter, and the transport coefficients of the quark–gluon plasma, among other parameters. Conversely, the latter capitalizes on the unparalleled pattern recognition capabilities of deep learning to discern robust features from high-dimensional raw data, specifically targeting individual physical parameters. This paper elucidates the fundamental principles of machine learning and delineates its potential to augment high-energy nuclear physics research endeavors.

Exploring electron transfer: Bioinspired, biomimetics, and bioelectrochemical systems for sustainable energy and Value-Added compound synthesis

Electron transfer (ET) is a fundamental process that underlies various phenomena in physics, chemistry, and biology. Understanding ET mechanisms is crucial for developing sustainable energy solutions and synthesizing value-added compounds efficiently. In this context, the present review provides the fundamental aspects of ET involving bioinspired, biomimetics, and biological entities and its significance for sustainable energy and green electrosynthesis fields. Among the theoretical and experimental cornerstones, Marcus Theory, electronic conductance, computational modeling, biomolecular thermodynamics, electrochemical and kinetic theories, protein film voltammetry, and the emergence of in situ and operando techniques are explored. Theoretical modeling is vital for understanding and predicting ET processes. Additionally, the significance of experimental techniques for investigating the ET process in biological entities and interfaces is discussed. Protein film voltammetry is a valuable and consolidated technique for studying ET processes at the protein-electrode interface, whereas in situ and operando techniques for interrogating ET processes in real time provide insights into the dynamics and mechanisms of ET. The concept of quantum conductance in biological structures is addressed, evidencing a trend and power of single-entity analysis. Aspects of extracellular and interfacial ET processes are presented and discussed in the electrochemical energy conversion systems. A deep understanding of these processes can improve the design of efficient bioinspired catalysts. Therefore, this multidisciplinary work aims to fill the gaps between different scientific fields related to ET involving bioentities to develop innovative energy and value-added compound synthesis solutions.

Dynamic compressive characteristics of a green sandstone under coupled hydraulic-mechanical loading: Experiments and theoretical modeling

Deep rock is under a complex geological environment with high geo-stress, high pore pressure, and strong dynamic disturbance. Understanding the dynamic response of rocks under coupled hydraulic-mechanical loading is thus essential in evaluating the stability and safety of subterranean engineering structures. Nevertheless, the constraints in experimental techniques have led to limited prior investigations into the dynamic compression behavior of rocks subjected to simultaneous high in-situ stress and pore pressure conditions. This study utilizes a triaxial split Hopkinson pressure bar (SHPB) system in conjunction with a pore pressure loading cell to conduct dynamic experiments on rocks subjected to hydraulic-mechanical loading. A porous green sandstone (GS) was adopted as the testing rock material. The findings reveal that the dynamic behavior of rock specimens is significantly influenced by multiple factors, including the loading rate, confining stress, and pore pressure. Specifically, the dynamic compressive strength of GS exhibits an increase with higher loading rates and greater confining pressures, while it decreases with elevated pore pressure. Moreover, the classical Ashby-Sammis micromechanical model was augmented to account for dynamic loading and pore pressure considerations. By deducing the connection between crack length and damage evolution, the resulting law of crack expansion rate is related to the strain rate. In addition, the influence of hydraulic factors on the stress intensity factor at the crack tip is introduced. Thereby, a dynamic constitutive model for deep rocks under coupled hydraulic-mechanical loading was established and then validated against the experimental results. Subsequently, the characteristics of introduced parameter for quantifying the water-induced effects were carefully discussed.

Dielectrophoretic motion of a red blood cell in a microfluidic environment: Insights from numerical simulations

This research delves into the dielectrophoresis (DEP) behavior of a biological cell within a sinusoidal-shaped microchannel utilizing the Maxwell stress tensor (MST) theory. A red blood cell (RBC), immersed in a viscoelastic fluid, is studied considering the Oldroyd-B model. The study aims to fill a gap in the literature by examining the DEP characteristics of RBC in a realistic geometric configuration and fluid environment, bridging the divide between theoretical modeling and practical application. This work uniquely explores the DEP behavior of an RBC within a sinusoidal microchannel in the presence of a viscoelastic flow regime, which simulates plasma properties, marking a novel contribution to the field. The two-dimensional numerical model incorporates the finite element method to accurately simulate the DEP effect and describe the behavior of the viscoelastic fluid. Validation results confirm the accuracy of the MST model. Crucially, numerical findings highlight the strong dependence of DEP force on electric potential and fluid permittivity. As a consequence of their heightened levels, there is an associated increase in both the DEP force and velocity. While the augmentation of fluid viscosity merely results in a deceleration of DEP velocity. The study provides valuable insights into the interplay between physical parameters and particle behavior, paving the way for advancements in microfluidic particle manipulation techniques.

Potential use of piezoelectric laser-induced vibration energy harvesting in wireless power transmission: Theoretical modelling and simulation

Because of continuous trend in wireless microdevice technology, a novel model of a laser-induced piezoelectric microgenerator within the framework of the non-Fourier heat conduction and nonlocal elasticity theory is proposed in this research. A non-Gaussian profile is considered for the laser source. The Galerkin method and the Laplace transform are employed to discretize and solve the coupled electro-thermo-mechanical equations, respectively. The inverse Laplace transform is numerically calculated to investigate the influences of the resistance load, laser intensity, laser absorption depth, specific heat capacity and thickness of the piezoelectric layer on the voltage response and power output of the microharvester. The obtained results reveal that the performance of the microharvester is dramatically affected by changing these parameters. Also, some optimum design parameters are provided to ensure the best performance of the system. Therefore, the present study can be helpful in analysis, design and optimization of wireless power devices, light-induced actuators and sensors in the future.

An equivalent modeling method for coupling stiffness of metal braided sleeve based on hyper-elastic material function

Abstract Metal hoses are important connecting components in pipelines, used for compensation in length and vibration reduction in system. Due to the complex structure of the metal braided sleeve on the outer layer of the metal hose and the nonlinear stiffness caused by coupling with the metal corrugated pipe during the combination process, modeling and calculation are difficult. In this paper, an equivalent modeling method for the coupling stiffness of metal braided sleeve based on Hyper-elastic material function is proposed. The parameters of Hyper-elastic material function are obtained through experiments. Experiments and simulations show that this method has a high accuracy, which propose an efficient way to solve the problems in theoretical analysis and simulation modeling of metal hose.

Application of Building Information Modeling (BIM) in the Planning and Construction of a Building

This paper aims to introduce Building Information Modeling (BIM) technology into the process of construction to achieve more efficient buildings, considering sustainability, economic improvements, reduced waste, and time optimization. The study involves the design, 3D modeling, planning, and monitoring of the work to assess the advantages and limitations of BIM through a real simulation. The methodology comprises theoretical foundations, 3D modeling, budgeting, and work monitoring. The project commenced with a 2D blueprint using Autodesk AutoCAD, followed by 3D modeling in Autodesk Revit. The resultant building, serving as an information system with a database and 3D modeling, allows for automated budgeting. The advantages of BIM encompass an interface between project and program, an interface between software, realistic renderings, precise material specifications, and family modeling. Limitations include the absence of material families, reformatting of Autodesk Revit tables when transferred to the Microsoft Excel program, generic family models with distorted renderings of reality, and heavy files. Despite these limitations, the implementation of BIM in buildings proves beneficial for projects. Collaborative work among stakeholders, optimization of project stages, and the reduction of expenses and rework can be achieved.

Preface

The Annual International Symposium on Physics and Applications (ISPA) is organized by the Department of Physics, Faculty of Sciences and Data Analytics at Institut Teknologi Sepuluh Nopember (ITS), Indonesia. Following the success of the 1st ISPA 2020 and the 2nd ISPA 2021, the 3rd ISPA, scheduled for November 22-23, 2023, aims to provide a platform for physicists to exchange ideas and engage in discussions at both the national and international levels. The event is generously supported by Airlangga University, the State University of Surabaya, and the National University of Singapore. The symposium features six keynote speakers and six invited speakers from various countries, including Japan, Turkey, Taiwan, Iraq, Saudi Arabia, Malaysia, and Indonesia. With a total of 51 full papers and 12 abstracts received for oral presentations, the selected contributions cover a wide range of research topics, including theoretical physics, modeling, computational physics, laser and optoelectronics, instrumentation and acoustics, earth sciences and geophysics, bio and medical physics, as well as material physics. Acknowledgments are extended to the advisory committee members, namely Suminar Pratapa, A. Rusydi, Madlazim, and G. Nabi, for their valuable contributions in creating a well-balanced scientific program. The organizers express their delight at the active participation of numerous graduate students and extend gratitude to the keynote and invited speakers, as well as all contributors to the 3rd ISPA 2023. Furthermore, the organizers express our gratitude to ITS for partially funding this conference. The organizers hope that the symposium will foster the initiation of research collaborations among participants, thereby supporting and enhancing the quality of research in the field of Physics and its applications, particularly within Indonesia. List of Organizing Committee, Keynote Speakers and Invited Speakers are available in this pdf.

Theoretical insights into the reduction of Azurin metal site with unnatural amino acid substitutions

Copper-containing proteins play crucial roles in biological systems. Azurin is a copper-containing protein which has a Type 1 copper site that facilitates electron transfer in the cytochrome chain. Previous research has highlighted the significant impact of mutations in the axial Met121 of the copper site on the reduction potential. However, the mechanism of this regulation has not been fully established. In this study, we employed theoretical modeling to investigate the reduction of the Type 1 copper site, focusing on how unnatural amino acid substitutions at Met121 influence its behavior. Our findings demonstrated a strong linear correlation between electrostatic interactions and the reduction potential of the copper site, which indicates that the perturbation of the reduction potential is primarily influenced by electrostatic interactions between the metal ion and the ligating atom. Furthermore, we found that CF/π and CF…H interactions could induce subtle changes in geometry and hence impact the electronic properties of the systems under study. In addition, our calculations suggest the coordination mode and ion-ligand distance could significantly impact the reduction potential of a copper site. Overall, this study offers valuable insights into the structural and electronic properties of the Type 1 copper site, which could potentially guide the design of future artificial catalysts.

A game theoretic conflict analysis model with linguistic assessments and two levels of game play

In a conflict scenario, the domestic and international stake holders vye to safeguard their specific vested interests and objectives, like in the Syrian and Afghan conflicts. Knowledge about the position of domestic players can help both domestic and international players determine the root causes of conflict and work in groups to resolve the divergent issues. Due to complex nature of conflicts, it is pertinent to study conflict at domestic and international levels separately. For this purpose, we design a two-level conflict analysis model based on game theory and linguistic assessments of players. The first level deals with local players by playing a game between each of them in view of local issues and taking into account the local grouping. At the second level, game is played between local groups and international players regarding multiple issues. In this way, all the parties calculate the gains or losses of comparable actions of each other. Thus, the proposed model provides a comprehensive study of conflict. This paper studies Syrian conflict to validate the conflict analysis algorithm and explain the computations and results.

Optimization of cooling rate of Q-P treated 42SiCr steel using AI digital twinning

In the continuously advancing field of mechanical engineering, digitalization is bringing a major transformation, specifically with the concept of digital twins. Digital twins are dynamic digital models of real-world systems and processes, crucial for Industry 4.0 and the emerging Industry 5.0, which are changing how humans and machines work together in manufacturing. This paper explores the combination of physics-based and data-driven modeling using advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques. This approach provides a comprehensive understanding of mechanical systems, improving materials design and manufacturing processes. The focus is on the advanced 42SiCr alloy, where AI-driven digital twinning is used to optimize cooling rates during Quenching and Partitioning (Q-P) treatments. This leads to significant improvements in the mechanical properties of 42SiCr steel. Given its complex properties influenced by various factors, this alloy is perfect for digital twinning. The Q-P heat treatment process not only restores the material's deformability but also gives it advanced high-strength steel (AHSS) properties. The findings show how AI and ML can effectively guide the development of high-strength steels and enhance their treatment processes. Additionally, integrating digital twins with new technologies like the Metaverse offers exciting possibilities for simulated production, remote monitoring, and collaborative design. By establishing a clear workflow from physical to digital twins and presenting empirical results, this paper connects theoretical modeling with practical applications, paving the way for smarter manufacturing solutions in mechanical engineering. Furthermore, this paper analyzes how digital twins can be integrated into advanced technologies like the Metaverse, opening up new possibilities for simulated production, remote monitoring, design collaboration, training simulations, analytics, and complete supply chain visibility. This integration is a crucial step toward realizing the full potential of digitalization in mechanical engineering.

Information Collection and Personalized Service Strategy of Monopoly under Consumer Misrepresentation

To decrease privacy risks, consumers may choose to misrepresent themselves when they are asked to offer personal information. Using a game theoretic model, this study examines the impact of consumer misrepresentation on both a monopolistic firm and consumers. The results show that consumer misrepresentation may benefit the firm, but hurt consumers under certain conditions. In addition, we find that when the unit cost of personalized service is low, consumer misrepresentation may encourage the firm to provide a higher personalized service level. Moreover, when consumers misrepresent themselves and the firm only covers part of the market, a greater unit value of consumer private information will reduce the firm’s profit, while a greater unit cost of personalized service will increase the firm’s profit. The analysis reported here provides important insights regarding the application of consumer information in online personalized marketing and consumer privacy protection.

Vimentin is a key regulator of cell mechanosensing through opposite actions on actomyosin and microtubule networks

The cytoskeleton is a complex network of interconnected biopolymers consisting of actin filaments, microtubules, and intermediate filaments. These biopolymers work in concert to transmit cell-generated forces to the extracellular matrix required for cell motility, wound healing, and tissue maintenance. While we know cell-generated forces are driven by actomyosin contractility and balanced by microtubule network resistance, the effect of intermediate filaments on cellular forces is unclear. Using a combination of theoretical modeling and experiments, we show that vimentin intermediate filaments tune cell stress by assisting in both actomyosin-based force transmission and reinforcement of microtubule networks under compression. We show that the competition between these two opposing effects of vimentin is regulated by the microenvironment stiffness. These results reconcile seemingly contradictory results in the literature and provide a unified description of vimentin’s effects on the transmission of cell contractile forces to the extracellular matrix.

Room Temperature Reduction of Nitrogen Oxide on Iron Metal-Organic Frameworks.

Nitrogen oxides represent one of the main threats for the environment. Despite decades of intensive research efforts, a sustainable solution for NOx removal under environmental conditions is still undefined. Using theoretical modelling, material design, state-of-the-art investigation methods and mimicking enzymes, it is found that selected porous hybrid iron(II/III) based MOF material are able to decompose NOx, at room temperature, in the presence of water and oxygen, into N2 and O2 and without reducing agents. This paves the way to the development of new highly sustainable heterogeneous catalysts to improve air quality.