Structural health monitoring : vibration-based damage detection and condition assessment of bridges

Structural health is a vital aspect of infrastructure sustainability. As a part of a vital infrastructure and transportation network, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs are a difficult burden for infrastructure owners. The structural health monitoring (SHM) systems proposed recently are incorporated with vibration-based damage detection techniques, statistical methods and signal processing techniques and have been regarded as efficient and economical ways to assess bridge condition and foresee probable costly failures. In this chapter, the recent developments in damage detection and condition assessment techniques based on vibration-based damage detection and statistical methods are reviewed. The vibration-based damage detection methods based on changes in natural frequencies, curvature or strain modes, modal strain energy, dynamic flexibility, artificial neural networks, before and after damage, and other signal processing methods such as Wavelet techniques, empirical mode decomposition and Hilbert spectrum methods are discussed in this chapter.

Assessment of damages for property damage

In Gagner Pty t/as Indochine Café v Canturi Corporation Pty Ltd (2009) 262 ALR 691, the assessment of damages awarded for the rectification work to the premises of the respondent was in issue. The appellant operated a restaurant above the respondent’s jewellery store in Sydney. When the kitchen of the restaurant flooded, water escaped causing damage to the jewellery store’s fit-out. The escape of the water was held to be due to the negligence of persons for whom the appellant was vicariously liable. The trial judge awarded damages, measured by the amount required to return the premises as close as was possible to the condition prior to the flood damage as well as an allowance for interruption to the business for 10 days. The 10 day allowance reflected the number of days the store would have been closed for if it was to be returned to its previous condition. The evidence was that the flooding has only affected approximately 10% of the floor area of the store. However, instead of having work carried out to bring the premises back to its condition as before the water damage, the respondent closed the business for 29 working days for a complete internal refurbishment – at a cost substantially more than simple rectification. On appeal it was argued that the trial judge had assessed the damages incorrectly as by undertaking a complete refurbishment had the effect that the respondent did not suffer any loss as a consequence of the negligence in relation to the fit-out. It was asserted that the claim for damages was in the circumstances a claim for betterment. It was also argued that the damages should not include a component for GST. Campbell JA gave reasons, with Macfarlan JA and Sackville AJA agreeing.

Field assessment of the resistance of timber products to termite (Isoptera) damage: Results can change with the amount of bait wood

Whether or not termites initiate damage to timber via the end grain may determine the need for spot-treating the exposed untreated cut ends of envelope-treated softwood framing material. Australian Coptotermes acinaciformis (Froggatt) were field-tested for their ability to initiate feeding via the end grain of timber (35 × 90 mm) treated with a repellent Tanalith® T envelope. Specimens of commercial radiata pine Pinus radiata D.Don framing timber (untreated) and slash pine Pinus elliottii Englem. (untreated and envelope-treated) were partially clad in fine stainless steel mesh. Clad and unclad specimens were exposed to C. acinaciformis near Townsville, North Queensland, Australia, for four months. Results showed that this species of termite can indeed damage timber via the end grain, including exposed untreated cut ends of envelope-treated material as demonstrated earlier for different populations of C. acinaciformis. Differences between the test conditions in field trials carried out at different times (where C. acinaciformis either did or did not damage timber via the end grain) are discussed. Clearly, outcomes from field studies with preservative-treated materials are dependent upon experimental conditions. Notably, the amount of bait wood (highly termite-susceptible timber substrate) offered in a given method can strongly influence the termite response. Further investigation is required to standardise this aspect of conditions in protocols for the assessment of wood preservatives.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

Experimental assessment of concrete damage due to exposure to high temperature and efficacy of the repair system

The present study experimentally evaluates the performance of control (standard cylinder specimen), damaged (mechanical loading after thermal exposure) and repaired / retrofitted normal plain concrete cylinders using different repair schemes such as on use of FRP wraps, Geo-polymers, etc., to restore the capacity of damaged structural concrete elements. The control-companion specimen in the series provides the reference frame against which both, specimen damage levels were quantified and the benefits of a specimen repaired subsequent to damage were assessed.

Literature Review of Integrated Impact Assessment Models of Climate Change with Emphasis on Damage Functions

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Real Time Concrete Damage Visual Assessment for First Responders

First responders are in danger when they perform tasks in damaged buildings after earthquakes. Structural collapse due to the failure of critical load bearing structural members (e.g. columns) during a post-earthquake event such as an aftershock can make first responders victims, considering they are unable to assess the impact of the damage inflicted in load bearing members. The writers here propose a method that can provide first responders with a crude but quick estimate of the damage inflicted in load bearing members. Under the proposed method, critical structural members (reinforced concrete columns in this study) are identified from digital visual data and the damage superimposed on these structural members is detected with the help of Visual Pattern Recognition techniques. The correlation of the two (e.g. the position, orientation and size of a crack on the surface of a column) is used to query a case-based reasoning knowledge base, which contains apriori classified states of columns according to the damage inflicted on them. When query results indicate the column's damage state is severe, the method assumes that a structural collapse is likely and first responders are warned to evacuate.

Assessment of DNA damage of Lewis lung carcinoma cells irradiated by carbon ions and X-rays using alkaline comet assay

DNA damage and cell reproductive death determined by alkaline comet and clonogenic survival assays were examined in Lewis lung carcinoma cells after exposure to 89.63 MeV/u carbon ion and 6 MV X-ray irradiations, respectively. Based on the survival data, Lewis lung carcinoma cells were verified to be more radiosensitive to the carbon ion beam than to the X-ray irradiation. The relative biological effectiveness (RBE) value, which was up to 1.77 at 10% survival level, showed that the DNA damage induced by the high-LET carbon ion beam was more remarkable than that induced by the low-LET X-ray irradiation. The dose response curves of '' Tail DNA (%)'' (TD) and "Olive tail moment" (OTM) for the carbon ion irradiation showed saturation beyond about 8 Gy. This behavior was not found in the X-ray curves. Additionally, the carbon ion beam produced a lower survival fraction at 2 Gy (SF2) value and a higher initial Olive tail moment 2 Gy (OTM2) than those for the X-ray irradiation. These results suggest that carbon ion beams having high-LET values produced more severe cell reproductive death and DNA damage in Lewis lung carcinoma cells in comparison with X-rays and comet assay might be an effective predictive test even combining with clonogenic assay to assess cellular radio sensitivity