scholarly journals FAILURE PROGNOSTICS BY A DATA-DRIVEN SIMILARITY-BASED APPROACH

2013 ◽  
Vol 20 (01) ◽  
pp. 1350001 ◽  
Author(s):  
FRANCESCO DI MAIO ◽  
ENRICO ZIO
Keyword(s):  
Monte Carlo ◽  
Crack Propagation ◽  
Crack Growth ◽  
Nonlinear Model ◽  
Particle Filtering ◽  
Growth Process ◽  
Estimation Method ◽  
Data Driven ◽  
Structural Components ◽  
Failure Prognostics

This paper presents a data-driven, similarity-based approach for prognostics of industrial and structural components. The potentiality of the approach is demonstrated on a problem of crack propagation, taken from literature. The crack growth process is described by a nonlinear model affected by nonadditive noises. A comparison is provided with an existing Monte Carlo-based estimation method, known as particle filtering.

Mechanical Behavior of Alumina Toughened Zirconia Nanocomposites with Different Alumina Additions

2014 ◽  
Vol 96 ◽  
pp. 61-66 ◽  
Author(s):  
Luis Antonio Díaz ◽  
Sergio Rivera ◽  
Adolfo Fernández ◽  
Anna Okunkova ◽  
Yu.G. Vladimirov ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Crack Propagation ◽  
Mechanical Behavior ◽  
Crack Growth ◽  
Disperse Phase ◽  
Subcritical Crack Growth ◽  
The Other ◽  
Structural Components ◽  
Monolithic Ceramics

ZrO2 and Al2O3 are monolithic ceramics used today in a wide variety of structural components. However, both materials present important drawbacks for some specific applications. In the case of Al2O3, its moderate strength (500 MPa) and toughness (4 MPa.√m) makes it unsuitable for high loading conditions. On the other hand, ZrO2 presents higher strength and toughness values (900 MPa and 6 MPa.√m) than Al2O3 but it is a material limited in its long-term behaviour due to its bad response to hydrothermal ageing and a pronounced tendency for subcritical crack growth. Due to this fact, ceramic nanocomposites made of Al2O3 and ZrO2 (ATZ and ZTA) have been developed in the last years in order to overcome the main drawbacks of the monolithic materials as they can combine the properties of both, strong and tough materials, simultaneously, with null ageing and even higher biocompatibility. In this work, several amounts of Al2O3 disperse phase (15, 35 and 50 vol %) were added to one ZrO2 matrix (CeO2 - 10 mol %) in order to see their effect on the mechanical properties, subcritical crack propagation and long-term reliability.

scholarly journals Fracture Nucleation Phenomena and Thermally Activated Crack Dynamics in Monocrystals

2021 ◽  
Vol 13 (1) ◽  
pp. 42
Author(s):  
Leonardo Golubović ◽  
Dorel Moldovan
Keyword(s):  
Monte Carlo ◽  
Crack Growth ◽  
Growth Process ◽  
Physical Review ◽  
Thermally Activated ◽  
Stochastic Nature ◽  
Monte Carlo Dynamics ◽  
Crack Dynamics ◽  
Dynamics Simulations ◽  
Fracture Nucleation

We explore irreversible thermally activated growth of cracks which are shorter than the Griffith length. Such a growth was anticipated in several studies [Golubović, L. & Feng, S., (1991). Rate of microcrack nucleation, Physical Review A 43, 5223. Golubović, L. & Peredera, A., (1995).  Mechanism of time-delayed fractures, Physical Review E 51, 2799]. We explore this thermally activated growth by means of atomistic Monte-Carlo dynamics simulations of stressed monocrystals. This crack growth is stepwise. Each step is marked by nucleation of a microcavity close to the crack tip, and by creation of a passage connecting the microcavity and the crack. If the external tensile stress is weak, many such nucleation events occur before the crack length reaches the Griffith size. In addition to the simulations, we also present an analytic theory of the stepwise thermally activated crack growth. The theory explains surprising observation form our simulations that the thermally activated crack growth remains fairly well directed in spite of the stochastic nature of the crack growth process.

scholarly journals Fatigue Crack Growth Analysis with Extended Finite Element for 3D Linear Elastic Material

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 397
Author(s):  
Yahya Ali Fageehi
Keyword(s):  
Finite Element ◽  
Fatigue Crack ◽  
Fatigue Life ◽  
Crack Propagation ◽  
Crack Growth ◽  
Mixed Mode ◽  
Propagation Path ◽  
Loading Conditions ◽  
Extended Finite Element ◽  
Linear Elastic

This paper presents computational modeling of a crack growth path under mixed-mode loadings in linear elastic materials and investigates the influence of a hole on both fatigue crack propagation and fatigue life when subjected to constant amplitude loading conditions. Though the crack propagation is inevitable, the simulation specified the crack propagation path such that the critical structure domain was not exceeded. ANSYS Mechanical APDL 19.2 was introduced with the aid of a new feature in ANSYS: Smart Crack growth technology. It predicts the propagation direction and subsequent fatigue life for structural components using the extended finite element method (XFEM). The Paris law model was used to evaluate the mixed-mode fatigue life for both a modified four-point bending beam and a cracked plate with three holes under the linear elastic fracture mechanics (LEFM) assumption. Precise estimates of the stress intensity factors (SIFs), the trajectory of crack growth, and the fatigue life by an incremental crack propagation analysis were recorded. The findings of this analysis are confirmed in published works in terms of crack propagation trajectories under mixed-mode loading conditions.

scholarly journals Multiple particle filtering for tracking wireless agents via Monte Carlo likelihood approximation

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Stephan Schlupkothen ◽  
Gerd Ascheid
Keyword(s):  
Monte Carlo ◽  
Computational Complexity ◽  
Particle Filtering ◽  
Gaussian Approximation ◽  
State Of The Art ◽  
Approximation Techniques ◽  
Accurate Localization ◽  
Likelihood Approximation ◽  
Current State ◽  
Multiple Particle

Abstract The localization of multiple wireless agents via, for example, distance and/or bearing measurements is challenging, particularly if relying on beacon-to-agent measurements alone is insufficient to guarantee accurate localization. In these cases, agent-to-agent measurements also need to be considered to improve the localization quality. In the context of particle filtering, the computational complexity of tracking many wireless agents is high when relying on conventional schemes. This is because in such schemes, all agents’ states are estimated simultaneously using a single filter. To overcome this problem, the concept of multiple particle filtering (MPF), in which an individual filter is used for each agent, has been proposed in the literature. However, due to the necessity of considering agent-to-agent measurements, additional effort is required to derive information on each individual filter from the available likelihoods. This is necessary because the distance and bearing measurements naturally depend on the states of two agents, which, in MPF, are estimated by two separate filters. Because the required likelihood cannot be analytically derived in general, an approximation is needed. To this end, this work extends current state-of-the-art likelihood approximation techniques based on Gaussian approximation under the assumption that the number of agents to be tracked is fixed and known. Moreover, a novel likelihood approximation method is proposed that enables efficient and accurate tracking. The simulations show that the proposed method achieves up to 22% higher accuracy with the same computational complexity as that of existing methods. Thus, efficient and accurate tracking of wireless agents is achieved.

scholarly journals Dynamic characteristics and fractal representations of crack propagation of rock with different fissures under multiple impact loadings

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bing Sun ◽  
Shun Liu ◽  
Sheng Zeng ◽  
Shanyong Wang ◽  
Shaoping Wang
Keyword(s):  
Fractal Dimension ◽  
Crack Propagation ◽  
Crack Growth ◽  
Impact Test ◽  
Fractal Theory ◽  
Dynamic Change ◽  
Fractal Dimensions ◽  
Peak Stress ◽  
Dynamic Mechanical Properties ◽  
Gravitational Potential Energy

AbstractTo investigate the influence of the fissure morphology on the dynamic mechanical properties of the rock and the crack propagation, a drop hammer impact test device was used to conduct impact failure tests on sandstones with different fissure numbers and fissure dips, simultaneously recorded the crack growth after each impact. The box fractal dimension is used to quantitatively analyze the dynamic change in the sandstone cracks and a fractal model of crack growth over time is established based on fractal theory. The results demonstrate that under impact test conditions of the same mass and different heights, the energy absorbed by sandstone accounts for about 26.7% of the gravitational potential energy. But at the same height and different mass, the energy absorbed by the sandstone accounts for about 68.6% of the total energy. As the fissure dip increases and the number of fissures increases, the dynamic peak stress and dynamic elastic modulus of the fractured sandstone gradually decrease. The fractal dimensions of crack evolution tend to increase with time as a whole and assume as a parabolic. Except for one fissure, 60° and 90° specimens, with the extension of time, the increase rate of fractal dimension is decreasing correspondingly.

scholarly journals Research on a novel data-driven aging estimation method for battery systems in real-world electric vehicles

2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110277
Author(s):  
Yankai Hou ◽  
Zhaosheng Zhang ◽  
Peng Liu ◽  
Chunbao Song ◽  
Zhenpo Wang
Keyword(s):  
Electric Vehicles ◽  
Real World ◽  
Regression Models ◽  
Estimation Method ◽  
Recursive Least Squares ◽  
Data Driven ◽  
Accurate Estimation ◽  
Support Vector ◽  
Battery Degradation ◽  
Operational Data

Accurate estimation of the degree of battery aging is essential to ensure safe operation of electric vehicles. In this paper, using real-world vehicles and their operational data, a battery aging estimation method is proposed based on a dual-polarization equivalent circuit (DPEC) model and multiple data-driven models. The DPEC model and the forgetting factor recursive least-squares method are used to determine the battery system’s ohmic internal resistance, with outliers being filtered using boxplots. Furthermore, eight common data-driven models are used to describe the relationship between battery degradation and the factors influencing this degradation, and these models are analyzed and compared in terms of both estimation accuracy and computational requirements. The results show that the gradient descent tree regression, XGBoost regression, and light GBM regression models are more accurate than the other methods, with root mean square errors of less than 6.9 mΩ. The AdaBoost and random forest regression models are regarded as alternative groups because of their relative instability. The linear regression, support vector machine regression, and k-nearest neighbor regression models are not recommended because of poor accuracy or excessively high computational requirements. This work can serve as a reference for subsequent battery degradation studies based on real-time operational data.

Sign in / Sign up

Export Citation Format

Share Document