International Journal of Non-Linear Mechanics最新文献

{"title":"Stability analysis of middle ear dynamic system after incudus joint repair under intense stimuli","authors":"Liang Wang ,&nbsp;Zhanli Liu ,&nbsp;Yongtao Sun ,&nbsp;Jie Wang ,&nbsp;Yueting Zhu ,&nbsp;Hongge Han ,&nbsp;Shuyi Xiang ,&nbsp;Qian Ding","doi":"10.1016/j.ijnonlinmec.2024.105011","DOIUrl":"10.1016/j.ijnonlinmec.2024.105011","url":null,"abstract":"<div><div>High intensity noise levels can lead to dislocation in the ossicular chain, particularly at the incus and the incudostapedial joint, significantly impacting hearing ability. However, the sensitivity of the middle ear system following ossicular chain restoration to intense external stimuli and the reconstructed material's nonlinear characteristics are still poorly understood. In order to investigate these aspects, a multi-degree-of-freedom mechanical model is developed on healthy and pathological ossicular chain reconstructions. Firstly, implant material parameters are determined by analyzing the natural frequencies of the system in an undamped condition. Secondly, the dynamic characteristics of the middle ear system are examined under various external excitations. Thirdly, utilizing a multi-time scale method, an approximate solution is derived for near-resonant frequency systems. Finally, the periodic solution stability is analyzed and assess how reconstructed middle ear parameters influence it. It is important to note that in healthy patients, post-ossicular chain reduction should be maintained in-ear sound pressure below 95 dB SPL, while for patients with pathology reconstruction, it should be kept below 65 dB SPL.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"171 ","pages":"Article 105011"},"PeriodicalIF":2.8,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143172061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scattering of anti-plane surface wave due to irregularity in hyperelastic imperfectly bonded bi-material structure","authors":"Md Hasanuzzaman ,&nbsp;Santan Kumar ,&nbsp;Richa Kumari","doi":"10.1016/j.ijnonlinmec.2024.105004","DOIUrl":"10.1016/j.ijnonlinmec.2024.105004","url":null,"abstract":"<div><div>The crux of this work is to investigate the scattering phenomena of Love-type wave due to irregularity on the upper surface of a layered structure. This structure basically incorporates two unlike nearly incompressible elastic materials which are bonded to each other imperfectly at the common interface between layer and half-space. The imperfect interface is described by linear spring model. The analytical methods which are applied, in order to derive the solution of displacement components and obtain the dispersion relations of Love-type wave, include variable separable method and substitution method along with perturbation technique. The dispersion relations and the expressions of displacement components of Love-type wave are obtained for both the incident and the scattered wave fields. Further, the expressions of reflected displacement fields of Love-type wave for distinct cases of irregularity, viz., rectangular shaped, parabolic shaped and triangular shaped irregularities, at the free surface are also determined. The derived results of dispersion relations and reflected displacement fields of Love-type wave, as particular case, concur well with the results existing in the literature. By means of numerical simulation, the influences of irregularity shapes and involved parameters, viz., irregularity depth, irregularity width and imperfect bonding parameter, on reflected displacement field of Love-type wave are manifested graphically. The impacts of imperfect bonding parameter and wave number on phase velocity of Love-type wave are also depicted. The computational results signify the substantial effects of irregularity at the free surface and imperfectness at the interface on the characteristics of Love-type wave in the considered nearly incompressible elastic structure. The reported results of the study may play pivotal role in the realm of civil, mechanical and earthquake engineering for the purpose of vibration isolation, shock absorber, flex-joints, engine mounts, and so forth.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 105004"},"PeriodicalIF":2.8,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonlinear vibration analysis of a fluid-conveying pipe under harmonic excitation with elastic boundary constraints","authors":"Yuanfeng Wu ,&nbsp;Enwei Chen ,&nbsp;Zhiwei Ruan ,&nbsp;Panpan Zhang ,&nbsp;Pin Chen ,&nbsp;Yimin Lu","doi":"10.1016/j.ijnonlinmec.2024.104981","DOIUrl":"10.1016/j.ijnonlinmec.2024.104981","url":null,"abstract":"<div><div>Fluid-conveying pipes are extensively used in practical engineering in various industries and play an important role in industry and daily life. Under complicated working conditions, inevitable vibrations affect the stability and integrity of these pipes, drawing significant academic attention. Typically, the dynamic modeling of these pipes considers ideal rigid boundary conditions, including fixed support, simply support, and cantilever pipes, ignoring the effects of boundary elasticity. This paper investigates the effects of boundary elasticity on the harmonic excitation responses in sub-critical and super-critical regimes. The governing equations and boundary conditions are derived via the extended Hamilton's principle. Later, the non-trivial equilibrium configuration is analytically deduced, and the governing equations for fluid-conveying pipes with elastic supports are discretized into a set of nonlinear ordinary differential equations using the Galerkin method. The harmonic balance method (HBM) is employed to solve these differential equations, with its accuracy validated against the Runge-Kutta method. Finally, numerical examples are conducted in sub-critical and super-critical regimes to show the effects of boundary vertical stiffness, torsional stiffness, fluid velocity, and excitation on solution stability, natural frequencies, and amplitude of the steady-state response at the middle point. This paper provides important guidance for the design of boundary elasticity in sub-critical and sup-critical fluid-conveying pipes.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 104981"},"PeriodicalIF":2.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling memory-driven dynamics: Fractional calculus and microswimmer trajectories in 1D shear flow","authors":"Elhoussine Azroul,&nbsp;Ghizlane Diki","doi":"10.1016/j.ijnonlinmec.2024.105005","DOIUrl":"10.1016/j.ijnonlinmec.2024.105005","url":null,"abstract":"<div><div>This study investigates the captivating dynamics of spherical microswimmers in a 1D shear flow, revealing the intricate interplay between memory effects and fluid mechanics through the lens of fractional calculus. By deriving exact solutions for the orientation and trajectory of these microswimmers, we uncover a rich tapestry of motion patterns that challenge traditional models. Our findings not only enhance the theoretical understanding of microswimmer behavior but also hold significant implications for practical applications in biophysics and targeted drug delivery. This research underscores the power of fractional calculus as a transformative tool in unraveling the complexities of biological systems, paving the way for innovative approaches in the study of fluid dynamics.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 105005"},"PeriodicalIF":2.8,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of 3D turbulent flows using a discretized generative model physics-informed neural networks","authors":"Amirhossein Khademi ,&nbsp;Erfan Salari ,&nbsp;Steven Dufour","doi":"10.1016/j.ijnonlinmec.2024.104988","DOIUrl":"10.1016/j.ijnonlinmec.2024.104988","url":null,"abstract":"<div><div>Physics-informed neural networks (PINNs) demonstrated efficacy in approximating partial differential equations (PDEs). However, challenges arise when dealing with high-dimensional PDEs, particularly when characterized by nonlinear and chaotic behavior, such as turbulent fluid flows. We introduce a novel methodology that integrates domain discretization, a generative model in the Sobolev function space (<span><math><msup><mrow><mi>H</mi></mrow><mrow><mn>1</mn></mrow></msup></math></span>), and a gating mechanism to effectively simulate high dimensional problems. The effectiveness of the method, Discretized Generative Model Physics-Informed Neural Networks (DG-PINN), is validated by its application to the simulation of a time-dependent 3D turbulent channel flow governed by the incompressible Navier–Stokes equations, a less explored problem in the existing literature. Domain discretization prevents error propagation by using different neural network models in different subdomains. The absence of initial conditions (IC) in subsequent time steps presents a challenge in identifying optimal network parameters. To address this, discretized generative models are used, improving the model’s overall performance. The global solutions’ regularity is enhanced compared to previous decomposition techniques by using the <span><math><msup><mrow><mi>H</mi></mrow><mrow><mn>1</mn></mrow></msup></math></span> norm of error, rather than <span><math><msup><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>. The effectiveness of the DG-PINN is validated through numerical test cases and compared against baseline PINNs and traditional domain decomposition PINNs. The DG-PINN demonstrates improvement in both approximation accuracy and computational efficiency, consistently maintaining accuracy even at later time instances. Moreover, the implementation of a distributed training strategy, facilitated by domain discretization, is discussed, resulting in improved convergence rates and more optimized memory usage.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 104988"},"PeriodicalIF":2.8,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven structural identification of nonlinear assemblies: Uncertainty Quantification","authors":"Sina Safari ,&nbsp;Diogo Montalvão ,&nbsp;Julián M. Londoño Monsalve","doi":"10.1016/j.ijnonlinmec.2024.105002","DOIUrl":"10.1016/j.ijnonlinmec.2024.105002","url":null,"abstract":"<div><div>Nonlinear model identification from vibration data is challenging due to limited measured data collected during the testing campaign and since the identified model should be capable of accounting for the uncertainties arising from the reassembly of the structure, environmental effects, and slight changes in parameters as a result of wear during vibration testing. In this paper, a new technique based on ensembling is proposed for uncertainty quantification during the identification of nonlinear assemblies using multiple data sets. First, an ensemble of parsimonious models is identified using a physics-informed nonlinear model identification method from subsets of measured data. Aggregate model statistics are then employed to calculate inclusion probabilities for the candidate model, which enable uncertainty quantification and a probabilistic estimate of the dynamic response. This results in a robust nonlinear model identification with physical interoperability. An application on a single-degree-of-freedom system idealised for an experimental structure with geometric and friction nonlinearities is presented. The results obtained demonstrate the substantial performance of the proposed technique in selecting accurate nonlinear models that capture the response over a large range of variability and repeatability for real-world data sets.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 105002"},"PeriodicalIF":2.8,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ML-based bevel gearbox fault diagnosis: An extensive time domain feature extraction approach with limited data","authors":"Sanjeev Kumar ,&nbsp;Om Prakash Singh ,&nbsp;Vikash Kumar ,&nbsp;Somnath Sarangi","doi":"10.1016/j.ijnonlinmec.2024.105003","DOIUrl":"10.1016/j.ijnonlinmec.2024.105003","url":null,"abstract":"<div><div>Data-driven based gear box fault diagnosis is one of the efficient approach as the gear drive train is highly nonlinear parametrically excited system. The data driven approach is solely dependent on the quality of the data acquired from the physical system. These data are direction-sensitive and carry different information depending on the state of the gearbox. In the literature, mostly one-directional data and their traditional time-domain feature matrix are utilized for gearbox fault diagnosis. The proposed work presents for the first time the effect of multi-directional data with a unique technique for data preparation based on various concatenation approaches. Along with this, the fifty extensive time domain features are extracted and fed to three different feature selection (FS) techniques and five popular machine learning (ML)-classifiers for fault diagnosis purposes. An experimental set-up with a bevel gearbox under different fault conditions was used to acquire the vibration signal data using a tri-axial accelerometer. The paper studies the three cases of data preparation: case 1: single-directional data at a time; case 2: horizontal concatenation of multi-directional data at a time; and case 3: vertical concatenation of multi-directional data at a time for gearbox fault diagnosis. Results show that overall, case 3 performed well and gave improved accuracy under different FS techniques and ML-classifiers as compared to cases 1 and 2.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 105003"},"PeriodicalIF":2.8,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A general framework for symplectic geometric integration for stochastically excited Hamiltonian systems on manifolds","authors":"Satyam Panda ,&nbsp;Souvik Chakraborty ,&nbsp;Budhaditya Hazra","doi":"10.1016/j.ijnonlinmec.2024.105001","DOIUrl":"10.1016/j.ijnonlinmec.2024.105001","url":null,"abstract":"<div><div>This work introduces a new integration scheme in the field of Stochastic Geometric Integration on Manifolds, dedicated to precise modeling of real-world dynamic phenomena characterized by inherent randomness. Conventional numerical techniques often encounter difficulties when confronted with uncertainty and the preservation of manifold geometry, consequently leading to inaccuracies. In response to these challenges, the method proposed considers geometric precision, stochastic dynamics, and symplecticity all-together. Drawing inspiration from methods based on Lie groups, this work formulates a framework that can adapt to stochastic systems, aligning itself with the principles of geometric stochastic differential equations. By incorporating higher-order geometric integration schemes possessing inherent symplectic properties, the study achieves accurate solutions that simultaneously retain intricate system geometry, maintain symplecticity, and accommodate inherent randomness. The method maintains its general flavor by virtue of a completely intrinsic formulation which can be adopted to broad class of manifolds rather than a specific one. Through numerous representative benchmarks, the study substantiates the effectiveness of the proposed scheme. The results demonstrate a significant enhancement in the numerical scheme’s performance, owing to its utilization of the inherent symplectic nature.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 105001"},"PeriodicalIF":2.8,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic dynamics analysis of quasi-partially integrable Hamiltonian system based on NN-SAM","authors":"Menglin Hu ,&nbsp;Wanrong Zan ,&nbsp;Wantao Jia ,&nbsp;Jiaojiao Sun","doi":"10.1016/j.ijnonlinmec.2024.104993","DOIUrl":"10.1016/j.ijnonlinmec.2024.104993","url":null,"abstract":"<div><div>Stochastic response and reliability analysis of quasi-partially integrable Hamiltonian systems are two important yet difficult problems due to high dimensionality and nonlinearity. Deep neural networks (DNNs) and the stochastic averaging method (SAM) can address the difficulty of system dimensionality in their own ways. This paper proposed a method called NN-SAM by merging physics-informed neural networks (PINNs) and SAM to solve the stochastic response and reliability of multi-dimensional quasi-partially integrable Hamiltonian systems. Firstly, by analyzing the resonance for quasi-partially integrable Hamiltonian systems, the averaged stochastic differential equations (SDEs) with less dimension for resonant and non-resonant cases through SAM are derived, respectively. Based on these averaged SDEs, the averaged Fokker–Planck–Kolmogorov (FPK) equation, the backward Kolmogorov (BK) equation and Pontryagin equation are obtained with mixed boundary conditions, including reflecting boundary, absorbing boundary or periodic boundary. Then, the PINNs are constructed for the response prediction and reliability assessment of the non-resonant case, including solving the averaged FPK equations, the BK equation and Pontryagin equation with or without periodic boundary conditions. For the resonant case, periodic layers are introduced as a hard constraint to the neural network to handle the periodic boundary conditions caused by resonance. Finally, two numerical examples are worked out and verified by the results from the Monte Carlo (MC) simulation. This work provides an effective technique for the stochastic response and reliability problems of quasi-partially integrable systems.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 104993"},"PeriodicalIF":2.8,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonlinear dynamic response of multi-satellite stack: Theoretical analysis and physical model experiments","authors":"Yuanheng Li ,&nbsp;Ruixiang Fan ,&nbsp;Fan Yang ,&nbsp;Hongjian Zhang ,&nbsp;Yu Luan ,&nbsp;Huiqiang Wu","doi":"10.1016/j.ijnonlinmec.2024.105007","DOIUrl":"10.1016/j.ijnonlinmec.2024.105007","url":null,"abstract":"<div><div>The development of low-orbit Internet constellations is a major priority in contemporary aerospace engineering, with the Multi-Satellite Stack emerging as a prominent method for high-capacity satellite deployment. This method involves a flat-panel satellite where adjacent layers of load-bearing columns are directly in contact, and uniform compression is applied through a connecting rod. The inherent multiple connection surfaces in this structure introduce complex nonlinear dynamic challenges. This study explores the lateral dynamic response of the Multi-Satellite Stack. By applying principles of structural composition, we develop theoretical models for the connection surfaces, load-bearing column stacks, connecting rods, and plates, accounting for parameters and state variables affected by slip. A comprehensive nonlinear dynamic model is derived from the force transmission relationships among these components. To validate the theoretical model, we design an equivalent physical model based on dynamic similarity criteria and conduct modal experiments and frequency response experiments to evaluate the effects of excitation amplitude and preload on assembly dynamics. The paper further examines the influence of structural parameters, including friction coefficient, elastic modulus of load-bearing columns and plates, on the assembly dynamics. This study provides a methodological framework for optimizing the structural design and stiffness matching requirements of the Multi-Satellite Stack in aerospace applications.</div></div>","PeriodicalId":50303,"journal":{"name":"International Journal of Non-Linear Mechanics","volume":"170 ","pages":"Article 105007"},"PeriodicalIF":2.8,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}