A local basis approximation approach for nonlinear parametric model order reduction

The efficient condition assessment of engineered systems requires the coupling of high fidelity models with data extracted from the state of the system `as-is'. In enabling this task, this paper implements a parametric Model Order Reduction (pMOR) scheme for nonlinear structural dynamics, and the particular case of material nonlinearity. A physics-based parametric representation is developed, incorporating dependencies on system properties and/or excitation characteristics. The pMOR formulation relies on use of a Proper Orthogonal Decomposition applied to a series of snapshots of the nonlinear dynamic response. A new approach to manifold interpolation is proposed, with interpolation taking place on the reduced coefficient matrix mapping local bases to a global one. We demonstrate the performance of this approach firstly on the simple example of a shear-frame structure, and secondly on the more complex 3D numerical case study of an earthquake-excited wind turbine tower. Parametric dependence pertains to structural properties, as well as the temporal and spectral characteristics of the applied excitation. The developed parametric Reduced Order Model (pROM) can be exploited for a number of tasks including monitoring and diagnostics, control of vibrating structures, and residual life estimation of critical components.Comment: 23 pages, 28 figure

Parametrized reduced order modeling for cracked solids

A parametrized reduced order modeling methodology for cracked two dimensional solids is presented, where the parameters correspond to geometric properties of the crack, such as location and size. The method follows the offline‐online paradigm, where in the offline, training phase, solutions are obtained for a set of parameter values, corresponding to specific crack configurations and a basis for a lower dimensional solution space is created. Then in the online phase, this basis is used to obtain solutions for configurations that do not lie in the training set. The use of the same basis for different crack geometries is rendered possible by defining a reference configuration and employing mesh morphing to map the reference to different target configurations. To enable the application to complex geometries, a mesh morphing technique is introduced, based on inverse distance weighting, which increases computational efficiency and allows for special treatment of boundaries. Applications in linear elastic fracture mechanics are considered, with the extended finite element method being used to represent discontinuous and asymptotic fields.ISSN:1097-0207ISSN:0029-598

Optical Coherence Tomography Image Analysis of Corneal Tissue

Because of the ubiquitous use of contact lenses, there is considerable interest in better understanding the anatomy of the cornea, the part of the eye in contact with an exterior lens. The recent technology developments in high resolution Optical Coherence Tomography (OCT) devices allows for the in-vivo observation of the structure of the human cornea in 3D and at cellular level resolution. Prolonged wear of contact lenses, inflammations, scarring and diseases can change the structure and physiology of the human cornea. OCT is capable of in-vivo, non-contact, 3D imaging of the human cornea. In this research, novel image processing algorithms were developed to process OCT images of the human cornea, in order to determine the corneal optical scattering and transmission. The algorithms were applied to OCT data sets acquired from multiple subjects before, during and after prolonged (3 hours) wear of soft contact lenses and eye patches, in order to investigate the changes in the corneal scattering associated with hypoxia. Results from this study demonstrate the ability of OCT to measure the optical scattering of corneal tissue and to monitor its changes resulting from external stress (hypoxia)

An adapted deflated conjugate gradient solver for robust extended/generalised finite element solutions of large scale, 3D crack propagation problems

An adapted deflation preconditioner is employed to accelerate the solution of linear systems resulting from the discretisation of fracture mechanics problems with well-conditioned extended/generalised finite elements. The deflation space typically used for linear elasticity problems is enriched with additional vectors, accounting for the enrichment functions used, thus effectively removing low frequency components of the error. To further improve performance, deflation is combined, in a multiplicative way, with a block-Jacobi preconditioner, which removes high frequency components of the error as well as near-linear dependencies introduced by enrichment. The resulting scheme is tested on a series of non-planar crack propagation problems and compared to alternative linear solvers in terms of performance

DEEP LEARNING BASED SURROGATE MODELLING OF WAVE PROPAGATION AND DAMAGE DETECTION IN CRACKED ROD

Guided wave-based Structural Health Monitoring (SHM) tools utilize the guided wave responses to interrogate damage in structures. This research demonstrates the use of various objective functions in single (mono) objective and multi-objective genetic algorithms for damage identification in isotropic 1D structures. The time domain spectral element method and a deep-learning-based surrogate is utilized for simulating wave propagation in an isotropic cracked rod. The genetic algorithms employ results ('numerical experiment') obtained from the spectral element model and the deep-learning-based surrogate to determine the optimized crack locations and crack depths as output parameters. The obtained optimized parameters from genetic algorithms are compared in terms of errors for various objective functions

Discrete and phase field methods for linear elastic fracture mechanics: a comparative study and state-of-the-art review

© 2019 by the authors. Three alternative approaches, namely the extended/generalized finite element method (XFEM/GFEM), the scaled boundary finite element method (SBFEM) and phase field methods, are surveyed and compared in the context of linear elastic fracture mechanics (LEFM). The purpose of the study is to provide a critical literature review, emphasizing on the mathematical, conceptual and implementation particularities that lead to the specific advantages and disadvantages of each method, as well as to offer numerical examples that help illustrate these features

Genomic medicine without borders: which strategies should developing countries employ to invest in precision medicine? A new "fast-second winner" strategy

Genomic medicine has greatly matured in terms of its technical capabilities, but the diffusion of genomic innovations worldwide faces significant barriers beyond mere access to technology. New global development strategies are sorely needed for biotechnologies such as genomics and their applications toward precision medicine without borders. Moreover, diffusion of genomic medicine globally cannot adhere to a “one-size-fits-all-countries” development strategy, in the same way that drug treatments should be customized. This begs a timely, difficult but crucial question: How should developing countries, and the resource-limited regions of developed countries, invest in genomic medicine? Although a full-scale investment in infrastructure from discovery to the translational implementation of genomic science is ideal, this may not always be feasible in all countries at all times. A simple “transplantation of genomics” from developed to developing countries is unlikely to be feasible. Nor should developing countries be seen as simple recipients and beneficiaries of genomic medicine developed elsewhere because important advances in genomic medicine have materialized in developing countries as well. There are several noteworthy examples of genomic medicine success stories involving resource-limited settings that are contextualized and described in this global genomic medicine innovation analysis. In addition, we outline here a new long-term development strategy for global genomic medicine in a way that recognizes the individual country's pressing public health priorities and disease burdens. We term this approach the “Fast-Second Winner” model of innovation that supports innovation commencing not only “upstream” of discovery science but also “mid-stream,” building on emerging highly promising biomarker and diagnostic candidates from the global science discovery pipeline, based on the unique needs of each country. A mid-stream entry into innovation can enhance collective learning from other innovators' mistakes upstream in discovery science and boost the probability of success for translation and implementation when resources are limited. This à la carte model of global innovation and development strategy offers multiple entry points into the global genomics innovation ecosystem for developing countries, whether or not extensive and expensive discovery infrastructures are already in place. Ultimately, broadening our thinking beyond the linear model of innovation will help us to enable the vision and practice of genomics without borders in both developed and resource-limited settings

Parametric reduced order models for output-only vibration-based crack detection in shell structures

ISSN:0888-3270ISSN:1096-121