Parametric probabilistic approach for cumulative fatigue damage using double linear damage rule considering limited data

International audienceThis work proposes a parametric probabilistic approach to model damage accumulation using the double linear damage rule (DLDR) considering the existence of limited experimental fatigue data. A probabilistic version of DLDR is developed in which the joint distribution of the knee-point coordinates is obtained as a function of the joint distribution of the DLDR model input parameters. Considering information extracted from experiments containing a limited number of data points, an uncertainty quantification framework based on the Maximum Entropy Principle and Monte Carlo simulations is proposed to determine the distribution of fatigue life. The proposed approach is validated using fatigue life experiments available in the literature

Empirical analysis and classification of database errors in Scopus and Web of Science

In the last decade, a growing number of studies focused on the qualitative/quantitative analysis of bibliometric-database errors. Most of these studies relied on the identification and (manual) examination of relatively limited samples of errors. Using an automated procedure, we collected a large corpus of more than 10,000 errors in the two multidisciplinary databases Scopus and Web of Science (WoS), mainly including articles in the Engineering-Manufacturing field. Based on the manual examination of a portion (of about 10%) of these errors, this paper provides a preliminary analysis and classification, identifying similarities and differences between Scopus and WoS. The analysis reveals interesting results, such as: (i) although Scopus seems more accurate than WoS, it tends to forget to index more papers, causing the loss of the relevant citations given/obtained, (ii) both databases have relatively serious problems in managing the so-called Online-First articles, and (iii) lack of correlation between databases, regarding the distribution of the errors in several error categories. The description is supported by practical examples concerning a variety of errors in the Scopus and WoS databases

Fatigue Test and Prognosis Study of Welded Tubular Joints in Signal Support Structures

Steel welded tubular joints have been widely used in traffic signal support structures for economic and aesthetic reasons. However, they are susceptible to fatigue cracking which may lead to structural failure such as collapse, thus pose a threat to driver's safety. To address this issue, this study is focused on fatigue test, modeling and prognosis of the fatigue crack growth in full-scale welded tubular joints of traffic signal support structures. Fatigue test of six full-scale welded tubular joint specimens fabricated based on real design for signal support structure is conducted to obtain crack growth data. Details of test setup and results are reported in this dissertation. Two types of fatigue crack growth models are proposed for two regimes of fatigue crack development in welded tubular joints: the linear elastic fracture mechanics (LEFM) model for the slow crack growth regime (denoted as Stage II here) and the empirical failure model for the rapid crack growth regime (denoted as Stage III). Details of these two models including their mathematical expressions, stochastic parameters, sensitivity analysis and model application, are given in the dissertation. A sensor-driven structural health prognosis procedure that has an explicit stochastic measurement error term and thus can model the sensor performance degradation over monitoring period is proposed. The prognosis procedure involves the Bayesian theorem and Markov Chain Monte Carlo (MCMC) sampling for updating the structural degradation model using sensor data. An extreme value theory (EVT) based tail fitting method is proposed to reduce the heavy burden on data transmission and computing involved in sensor driven prognosis. This method employs moment estimator to calculate the small quantiles of the prognosis results by using a small portion of available sensor data. Finally, fatigue test data acquired in this study are used to examine the proposed fatigue life prognosis procedure. Both the LEFM based fatigue crack growth model and the empirical failure model are studied for fatigue life prognosis application. Prognosis results show that the prognosis procedure is able to provide good estimate of the fatigue crack growth curve of welded tubular joints in signal support structures if certain conditions are met

Evaluation of Information Entropy from Acoustic Emission Waveforms as a Fatigue Damage Metric for Al7075-T6

Information entropy measured from acoustic emission (AE) waveforms is shown to be an indicator of fatigue damage in a high-strength aluminum alloy. Several tension-tension fatigue experiments were performed with dogbone samples of aluminum alloy, Al7075-T6, a commonly used material in aerospace structures. Unlike previous studies in which fatigue damage is simply measured based on visible crack growth, this work investigated fatigue damage prior to crack initiation through the use of instantaneous elastic modulus degradation. Three methods of measuring the AE information entropy, regarded as a direct measure of microstructural disorder, are proposed and compared with traditional damage-related AE features. Results show that one of the three entropy measurement methods appears to better assess damage than the traditional AE features, while the other two entropies have unique trends that can differentiate between small and large cracks

Entropic Approaches for Assessment of Metal Fatigue Damage

Prognostics and Health Management (PHM), a promising technique assessing individual life of engineering systems, requires metrics that indicate the current level of degradation and aging. However, traditional methods of fatigue life estimation have a restriction to apply to PHM due to scale dependency of measurements. An alternative to the conventional fatigue assessment is the entropic approach, initially de-rived from the second law of thermodynamics. The entropic approach is scale-independent and able to monitor degradation and aging from the early periods of life. The entropic endurance indicates a certain level of damage that a component can tolerate before failure. Not only the thermodynamic theory but also information and statistical mechanics laws introducing entropy apply to the various modes of energy dissipations. This dissertation introduces the extension of the entropic approaches as the representation of damage by empirically examining the theoretical basis of three en-tropic theorems. Metallic coupons were fatigue tested to confirm the applicability of three entropic measures: irreversible thermodynamic entropy, information (Shannon) entropy, and Jeffreys divergence, by measuring variables used to compute energy dissipations during fatigue. In addition to the entropic approaches to damage, short-term loading process (STLP) is designed to minimize the difficulties associated with acoustic emission background noise when used to measure information entropy of the generated signals. Without damaging the material, high-frequency/low-amplitude loading is expected to generate acoustic signals through quiet background noise excitation loading to infer the current damage status. The results of this research help identifying multiple damage measurement methods and will broaden understanding and selecting practical applications, and reduce the prognosis uncertainty in PHM applications