Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Linear and Nonlinear Guided Wave Imaging of Impact Damage in CFRP Using a Probabilistic Approach.

ABSTRACT: The amount and variety of composite structures that need to be inspected for the presence of impact damage has grown significantly in the last few decades. In this paper, an application of a probabilistic ultrasonic guided wave imaging technique for impact damage detection in carbon fiber-reinforced polymers (CFRP) is presented. On the one hand, a linear, baseline-dependent, technique utilizing the well-known correlation-based RAPID method and an array of piezoelectric transducers is applied to detect impact-induced damage in plate-like composite structures. Furthermore, a baseline-independent nonlinear extension of the standard RAPID method is proposed, and its performance is demonstrated both numerically and experimentally. Compared to the conventional RAPID, the baseline-free version suffers from a somewhat lower imaging quality. However, this drawback is compensated by the fact that no damage-free (intact) baseline is necessary for successful imaging of damage.

SUBMITTER: Hettler J

PROVIDER: S-EPMC5457249 | biostudies-other | 2016 Nov

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

Characterizing Hypervelocity Impact (HVI)-Induced Pitting Damage Using Active Guided Ultrasonic Waves: From Linear to Nonlinear.

Project description:Hypervelocity impact (HVI), ubiquitous in low Earth orbit with an impacting velocity in excess of 1 km/s, poses an immense threat to the safety of orbiting spacecraft. Upon penetration of the outer shielding layer of a typical two-layer shielding system, the shattered projectile, together with the jetted materials of the outer shielding material, subsequently impinge the inner shielding layer, to which pitting damage is introduced. The pitting damage includes numerous craters and cracks disorderedly scattered over a wide region. Targeting the quantitative evaluation of this sort of damage (multitudinous damage within a singular inspection region), a characterization strategy, associating linear with nonlinear features of guided ultrasonic waves, is developed. Linear-wise, changes in the signal features in the time domain (e.g., time-of-flight and energy dissipation) are extracted, for detecting gross damage whose characteristic dimensions are comparable to the wavelength of the probing wave; nonlinear-wise, changes in the signal features in the frequency domain (e.g., second harmonic generation), which are proven to be more sensitive than their linear counterparts to small-scale damage, are explored to characterize HVI-induced pitting damage scattered in the inner layer. A numerical simulation, supplemented with experimental validation, quantitatively reveals the accumulation of nonlinearity of the guided waves when the waves traverse the pitting damage, based on which linear and nonlinear damage indices are proposed. A path-based rapid imaging algorithm, in conjunction with the use of the developed linear and nonlinear indices, is developed, whereby the HVI-induced pitting damage is characterized in images in terms of the probability of occurrence.

| S-EPMC5459012 | biostudies-other

Dataset for surface and internal damage after impact on CFRP laminates.

Project description:Various foreign objects can collide with CFRP structures, such as CFRP aircraft. Once something impacts with CFRP laminates, both surface damage and internal damage can occur. Even if the external damage is such invisible as called barely visible impact damage, there are matrix cracks or delamination that are the main cause of compressive strength reduction, so it is difficult to find the relationship between external and internal damage on CFRP laminates. This dataset is prepared for predicting impact information only from surface damage profiles using Machine Learning (Hasebe et al., 2022). It includes three data, surface damage image (png), surface depth contour image(png), and internal damage image after ultrasound C-scanning (jpg) after low-velocity impact testing under various impact conditions. The data are helpful for researchers and engineers who deal with the impact behavior of CFRP or data science.

| S-EPMC9294053 | biostudies-literature

Femtosecond laser axotomy in Caenorhabditis elegans and collateral damage assessment using a combination of linear and nonlinear imaging techniques.

Project description:In this work highly localized femtosecond laser ablation is used to dissect single axons within a living Caenorhabditis elegans (C. elegans). We present a multimodal imaging methodology for the assessment of the collateral damage induced by the laser. This relies on the observation of the tissues surrounding the targeted region using a combination of different high resolution microscopy modalities. We present the use of Second Harmonic Generation (SHG) and Polarization Sensitive SHG (PSHG) to determine damage in the neighbor muscle cells. All the above is done using a single instrument: multimodal microscopy setup that allows simultaneous imaging in the linear and non-linear regimes and femtosecond-laser ablation.

| S-EPMC3590135 | biostudies-literature

Non-Destructive Thermography Analysis of Impact Damage on Large-Scale CFRP Automotive Parts.

Project description:Laminated composites are increasingly used in aeronautics and the wind energy industry, as well as in the automotive industry. In these applications, the construction and processing need to fulfill the highest requirements regarding weight and mechanical properties. Environmental issues, like fuel consumption and CO₂-footprint, set new challenges in producing lightweight parts that meet the highly monitored standards for these branches. In the automotive industry, one main aspect of construction is the impact behavior of structural parts. To verify the quality of parts made from composite materials with little effort, cost and time, non-destructive test methods are increasingly used. A highly recommended non-destructive testing method is thermography analysis. In this work, a prototype for a car's base plate was produced by using vacuum infusion. For research work, testing specimens were produced with the same multi-layer build up as the prototypes. These specimens were charged with defined loads in impact tests to simulate the effect of stone chips. Afterwards, the impacted specimens were investigated with thermography analysis. The research results in that work will help to understand the possible fields of application and the usage of thermography analysis as the first quick and economic failure detection method for automotive parts.

| S-EPMC5453135 | biostudies-other

Nonlinear Guided Wave Tomography for Detection and Evaluation of Early-Life Material Degradation in Plates.

Project description:In this paper, the possibility of using nonlinear ultrasonic guided waves for early-life material degradation in metal plates is investigated through both computational modeling and study. The analysis of the second harmonics of Lamb waves in a free boundary aluminum plate, and the internal resonance conditions between the Lamb wave primary modes and the second harmonics are investigated. Subsequently, Murnaghan's hyperelastic model is implemented in a finite element (FE) analysis to study the response of aluminum plates subjected to a 60 kHz Hanning-windowed tone burst. Different stages of material degradation are reflected as the changes in the third order elastic constants (TOECs) of the Murnaghan's model. The reconstructed degradations match the actual ones well across various degrees of degradation. The effects of several relevant factors on the accuracy of reconstructions are also discussed.

| S-EPMC8402285 | biostudies-literature

MALDI-imaging-guided transcriptomics

Project description:MALDI-imaging-guided Transcriptomics

| PRJEB69276 | ENA

Correcting the linear and nonlinear distortions for atomically resolved STEM spectrum and diffraction imaging.

Project description:Specimen and stage drift as well as scan distortions can lead to a mismatch between true and desired electron probe positions in scanning transmission electron microscopy (STEM) which can result in both linear and nonlinear distortions in the subsequent experimental images. This problem is intensified in STEM spectrum and diffraction imaging techniques owing to the extended dwell times (pixel exposure time) as compared to conventional STEM imaging. As a consequence, these image distortions become more severe in STEM spectrum/diffraction imaging. This becomes visible as expansion, compression and/or shearing of the crystal lattice, and can even prohibit atomic resolution and thus limits the interpretability of the results. Here, we report a software tool for post-correcting the linear and nonlinear image distortions of atomically resolved 3D spectrum imaging as well as 4D diffraction imaging. This tool improves the interpretability of distorted STEM spectrum/diffraction imaging data.

| S-EPMC6025237 | biostudies-literature

Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models.

Project description:Partially linear models provide a useful class of tools for modeling complex data by naturally incorporating a combination of linear and nonlinear effects within one framework. One key question in partially linear models is the choice of model structure, that is, how to decide which covariates are linear and which are nonlinear. This is a fundamental, yet largely unsolved problem for partially linear models. In practice, one often assumes that the model structure is given or known and then makes estimation and inference based on that structure. Alternatively, there are two methods in common use for tackling the problem: hypotheses testing and visual screening based on the marginal fits. Both methods are quite useful in practice but have their drawbacks. First, it is difficult to construct a powerful procedure for testing multiple hypotheses of linear against nonlinear fits. Second, the screening procedure based on the scatterplots of individual covariate fits may provide an educated guess on the regression function form, but the procedure is ad hoc and lacks theoretical justifications. In this article, we propose a new approach to structure selection for partially linear models, called the LAND (Linear And Nonlinear Discoverer). The procedure is developed in an elegant mathematical framework and possesses desired theoretical and computational properties. Under certain regularity conditions, we show that the LAND estimator is able to identify the underlying true model structure correctly and at the same time estimate the multivariate regression function consistently. The convergence rate of the new estimator is established as well. We further propose an iterative algorithm to implement the procedure and illustrate its performance by simulated and real examples. Supplementary materials for this article are available online.

| S-EPMC3222957 | biostudies-literature

Linear-nonlinear cascades capture synaptic dynamics.

Project description:Short-term synaptic dynamics differ markedly across connections and strongly regulate how action potentials communicate information. To model the range of synaptic dynamics observed in experiments, we have developed a flexible mathematical framework based on a linear-nonlinear operation. This model can capture various experimentally observed features of synaptic dynamics and different types of heteroskedasticity. Despite its conceptual simplicity, we show that it is more adaptable than previous models. Combined with a standard maximum likelihood approach, synaptic dynamics can be accurately and efficiently characterized using naturalistic stimulation patterns. These results make explicit that synaptic processing bears algorithmic similarities with information processing in convolutional neural networks.

| S-EPMC7993773 | biostudies-literature

Nonlinear optical components for all-optical probabilistic graphical model.

Project description:The probabilistic graphical models (PGMs) are tools that are used to compute probability distributions over large and complex interacting variables. They have applications in social networks, speech recognition, artificial intelligence, machine learning, and many more areas. Here, we present an all-optical implementation of a PGM through the sum-product message passing algorithm (SPMPA) governed by a wavelength multiplexing architecture. As a proof-of-concept, we demonstrate the use of optics to solve a two node graphical model governed by SPMPA and successfully map the message passing algorithm onto photonics operations. The essential mathematical functions required for this algorithm, including multiplication and division, are implemented using nonlinear optics in thin film materials. The multiplication and division are demonstrated through a logarithm-summation-exponentiation operation and a pump-probe saturation process, respectively. The fundamental bottlenecks for the scalability of the presented scheme are discussed as well.

| S-EPMC5974078 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data