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Oil flowlines, the first “pipeline” system connected to the wellhead, are pipelines that are 5 to 30.5 cm (two to twelve inches) in diameter, most susceptible to corrosion, and very difficult to inspect. Herein, an external corrosion detection sensor for oil and gas pipelines, consisting of a semicircular plastic strip, a flat dog-bone-shaped sacrificial metal plate made out of the same pipeline material, and an optical fiber with Fiber Bragg Grating (FBG) sensors, is described. In the actual application, multiple FBG optical fibers are attached to an oil and gas pipeline using straps or strips or very large hose clamps, and, every few meters, our proposed corrosion detection sensor will be glued to the FBG sensors. When the plastic parts are attached to the sacrificial metals, the plastic parts will be deformed and stressed; thus, placing the FBG sensors in tension. When corrosion is severe at any given pipeline location, the sacrificial metal at that location will corrode till failure and the tension strain is relieved at that FBG Sensor location, and therefore, a signal is detected at the interrogator. Herein, the external corrosion detection sensor and its design equations are described, and experimental results, verifying our theory, are presented.

In this work we investigate the appearance of post-resonance backward whirl (Po-BW) using the model of a rotor with a breathing crack. This phenomenon could be employed as an indicator of crack in rotor systems that pass through critical forward whirl rotational speed during startup and coast down operations. The Finite Element Model (FEM) is used to develop the linear-time-varying (LTV) equations of motion of the considered accelerating cracked rotor. The whirl response is obtained by direct numerical integration. In addition, the effect of bearing anisotropy on Po-BW excitation is investigated. It is found that the appearance of Po-BW zones is significantly affected by the depth of the crack, angular acceleration rate, anisotropy of bearings, and the orientation of the unbalance force vector with respect to the crack opening direction. In addition, the full spectrum analysis is found to be an efficient tool for identifying the Po-BW zones of rotational speeds in the whirl response.

A monitoring solution was developed for detection of material loss in metals such as carbon steel using the force generated by permanent magnets in addition to the optical strain sensing technology. The working principle of the sensing system is related to the change in thickness of a steel plate, which typically occurs due to corrosion. As thickness decreases, the magnetostatic force between the magnet and the steel structure also decreases. This, in turn, affects the strain measured using the optical fiber. The sensor prototype was designed and built after verifying its sensitivity using a numerical model. The prototype was tested on steel plates of different thicknesses to establish the relationship between the metal thickness and measured strain. The results of experiments and numerical models demonstrate a strong relationship between the metal thickness and the measured strain values.

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.

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This article describes detection of structural damage using statistical properties of randomdec signatures. Proposed technique is model free and does not require input measurements. The technique is evaluated using acceleration data obtained from a finite element model of a frame-like structure. Damage in the model is represented by a structural member with nonlinear stiffness characteristic due to opening and closing cracks. The results suggest that reliability of damage detection would depend on the orientation of the crack and the richness of the response. described in previously cited publications [1][2][3][4] were developed with the assumption of linearity of the structures and the changes that occur in them due to degradation. However, this is not necessarily the case in reality since structural damage introduces nonlinearity [5]. For example, beams containing breathing fatigue cracks would have displacement-dependent stiffness and are modeled as structures with bilinear stiffness characteristics [6]. Therefore, introduction of nonlinearities and other nonlinear phenomena could be exploited for structural health monitoring (SHM) purposes.Recently, some researchers started developing SHM methods that utilize nonlinear phenomena. Hunter [7] used an ARMA-based time series approach to characterize a system with bilinear stiffness characteristics. Different response regions were described by separate linear models. The authors were able to detect changes in the identified natural frequencies and mode shapes based on the obtained models. Another technique developed by Epureanu and Yin [8] exploited changes in the probability density functions of sampled attractors of an aeroelastic system. Adams and Nataraju [9] and Brown and Adams [10] proposed the use of nonlinear loworder state space models for damage variables.Nichols et al. [11,12] investigated the use of attractor dimension as a feature for SHM and compared different metrics reflecting attractor dimension. Moniz et al. [13] and Todd et al. [14] monitored the changes in the attractor formed from exciting the system by the output of a Lorenz oscillator. The assumption is that the system in a healthy state is a linear filter, although changes in the system (being linear or not) would cause the changes in the attractor.Chen et al.[15] studied degradation of reinforced concrete beams and discovered that their dynamic behavior was close to that of Duffing oscillator with softening stiffness. The authors developed a damage indicator based on the difference between the resonant frequencies obtained from dynamic tests with increasing and decreasing excitation frequencies. Wang et al.[16] defined a damage indicator based on coherence function that is sensitive to the onset of nonlinearity. The authors successfully detected damage in a steel frame. Thus, nonlinear response features can be useful indicators of damage.The goal of this work is to demonstrate a new SHM method based on changes in statistical properties of randomdec signatures caused by the onset of nonlin...