1,720,974 research outputs found
Reduced order modelling of the non-linear stiffness in MEMS resonators
No full textWe propose a simplified numerical technique to quantify the effects of non-linear stiffness in MEMS resonators and we validate our approach on a clamped-clamped beam, a softening Disk Ring Gyroscope (DRG) and a shallow arch showing internal resonance. We generate a Reduced Order Model (ROM) which is integrated with either a direct integration approach or a continuation technique with arc length control. Finally we compare and validate the results with a full FEM model
SHM and Efficient Strategies for Reduced-Order Modeling
Full text linkWithin model-based approaches to structural health monitoring (SHM), numerical simulations must be tailored to continuously adapt to the degradation processes and to the possibly changing environment. This model update stage of the analysis brings two competing requirements: the accuracy of the model, with a more detailed description of the phenomena required where damage is supposed to take place; the efficiency of the model, to reduce the overall computational burden and allow for real-time (or close to real-time) computing. Without resorting to AI-based strategies, approaches solely based on proper orthogonal decomposition (POD) and domain decomposition (DD) techniques proved rather efficient in handling the aforementioned trade-off between the diverging requirements of accuracy and efficiency. In this work, we discuss a further improvement over our recently proposed methodology that consists of: a DD of the entire structure into sub-regions, which can be designed to decouple regions more prone to get damaged from regions that are instead less affected by the degradation processes; a POD-based selective model order reduction for all the domains, with adjustable and heterogeneous accuracy requirements. The approach is assessed through an illustrative example related to beam dynamics, with results provided in terms of both accuracy and computational efficiency, or speedup with respect to the full-order model
Interpolation Based Reduced Order Modelling for Non-linearities in MEMS
No full textIn this paper a numerical Reduced Order Modelling (ROM) procedure able to simulate Micro-Electrical-Mechanical-Systems (MEMS) devices featuring electrostatic and geometric non-linearities is proposed. The main idea is to model MEMS devices as composition of stiff components, compliant elements and electrodes. Consequently, the problem dimensionality is determined by the degrees of freedom (dof) of the stiff components. Elastic and electrostatic forces are modelled through a mapping procedure that consists in the interpolation or fitting of numerically precomputed tables. The ROM is applied to the analysis of a MEMS quad-mass structure and validated with experimental data
Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches
Full text linkMicro-Electro-Mechanical-Systems are complex structures, often involving
nonlinearites of geometric and multiphysics nature, that are used as sensors
and actuators in countless applications. Starting from full-order
representations, we apply deep learning techniques to generate accurate,
efficient and real-time reduced order models to be used as virtual twin for the
simulation and optimization of higher-level complex systems. We extensively
test the reliability of the proposed procedures on micromirrors, arches and
gyroscopes, also displaying intricate dynamical evolutions like internal
resonances. In particular, we discuss the accuracy of the deep learning
technique and its ability to replicate and converge to the invariant manifolds
predicted using the recently developed direct parametrization approach that
allows extracting the nonlinear normal modes of large finite element models.
Finally, by addressing an electromechanical gyroscope, we show that the
non-intrusive deep learning approach generalizes easily to complex multiphysics
problem
Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions
Full text linkHighly accurate simulations of complex phenomena governed by partial
differential equations (PDEs) typically require intrusive methods and entail
expensive computational costs, which might become prohibitive when
approximating steady-state solutions of PDEs for multiple combinations of
control parameters and initial conditions. Therefore, constructing efficient
reduced order models (ROMs) that enable accurate but fast predictions, while
retaining the dynamical characteristics of the physical phenomenon as
parameters vary, is of paramount importance. In this work, a data-driven,
non-intrusive framework which combines ROM construction with reduced dynamics
identification, is presented. Starting from a limited amount of full order
solutions, the proposed approach leverages autoencoder neural networks with
parametric sparse identification of nonlinear dynamics (SINDy) to construct a
low-dimensional dynamical model. This model can be queried to efficiently
compute full-time solutions at new parameter instances, as well as directly fed
to continuation algorithms. These aim at tracking the evolution of periodic
steady-state responses as functions of system parameters, avoiding the
computation of the transient phase, and allowing to detect instabilities and
bifurcations. Featuring an explicit and parametrized modeling of the reduced
dynamics, the proposed data-driven framework presents remarkable capabilities
to generalize with respect to both time and parameters. Applications to
structural mechanics and fluid dynamics problems illustrate the effectiveness
and accuracy of the proposed method
Investigation of Quasi-Periodic Solutions in Nonlinear Oscillators Featuring Internal Resonance
No full textQuasi-periodic solutions can arise in assemblies of nonlinear oscillators as a consequence of Neimark--Sacker (NS) bifurcations. In this chapter, we investigate analytically and numerically the system of two coupled oscillators in two different settings featuring 1:2 and 1:3 internal resonances, respectively. More specifically, in the former case, the locus of NS points is obtained analytically, and its variation with respect to the system parameters is highlighted. In the latter case, on the contrary, the NS boundary curve is investigated numerically. In both cases, the results allow predicting the appearance of quasi-periodic solutions
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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