999 resultados para Typical damage
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Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.
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A total histological grade does not necessarily distinguish between different manifestations of cartilage damage or degeneration. An accurate and reliable histological assessment method is required to separate normal and pathological tissue within a joint during treatment of degenerative joint conditions and to sub-classify the latter in meaningful ways. The Modified Mankin method may be adaptable for this purpose. We investigated how much detail may be lost by assigning one composite score/grade to represent different degenerative components of the osteoarthritic condition. We used four ovine injury models (sham surgery, anterior cruciate ligament/medial collateral ligament instability, simulated anatomic anterior cruciate ligament reconstruction and meniscal removal) to induce different degrees and potentially 'types' (mechanisms) of osteoarthritis. Articular cartilage was systematically harvested, prepared for histological examination and graded in a blinded fashion using a Modified Mankin grading method. Results showed that the possible permutations of cartilage damage were significant and far more varied than the current intended use that histological grading systems allow. Of 1352 cartilage specimens graded, 234 different manifestations of potential histological damage were observed across 23 potential individual grades of the Modified Mankin grading method. The results presented here show that current composite histological grading may contain additional information that could potentially discern different stages or mechanisms of cartilage damage and degeneration in a sheep model. This approach may be applicable to other grading systems.
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The Black rat (Rattus rattus), a serious pest of Australian macadamia orchards has been estimated to cause up to 30% crop damage in Australian orchards. In recent years an increase in the number of commercially available cultivars has seen a change in orchard characteristics in Australia, primarily effecting fruiting and flowering patterns. This has been suggested to affect the feeding behaviour of rodents and in turn altered the damage process. In this study we compare the extent of damage in orchards containing one of three prevalent cultivars (A4/A16, A268 and HAES 344/741) and investigate the influence of these cultivars, particularly their distinctive fruiting traits, on rodent damage within the orchard. We demonstrate that the temporal pattern and extent of damage differs between cultivar types. Newer Australian macadamia cultivars tested in this study were found to be far more susceptible to rodent damage than the older Hawaiian developed cultivars, most likely due to an extended fruiting period and thinner shells. This has resulted in a more sustained period of crop damage than the patterns of crop damage observed in previous Australian studies. Crop damage caused by R. rattus is significantly higher in orchards that maintain high levels of canopy resources through the fruiting season and we postulate that this is due to the extended fruiting periods of the new cultivars used. The maintenance of canopy resource load in turn corresponds to high crop damage, in this study resulting in crop losses of up to 25%.
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In this paper, a three-dimensional nonlinear rigid body model has been developed for the investigation of the crashworthiness of a passenger train using the multibody dynamics approach. This model refers to a typical design of passenger cars and train constructs commonly used in Australia. The high-energy and low-energy crush zones of the cars and the train constructs are assumed and the data are explicitly provided in the paper. The crash scenario is limited to the train colliding on to a fixed barrier symmetrically. The simulations of a single car show that this initial design is only applicable for the crash speed of 35 km/h or lower. For higher speeds (e.g. 140 km/h), the crush lengths or crush forces or both the crush zone elements will have to be enlarged. It is generally better to increase the crush length than the crush force in order to retain the low levels of the longitudinal deceleration of the passenger cars.
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This paper presents two novel concepts to enhance the accuracy of damage detection using the Modal Strain Energy based Damage Index (MSEDI) with the presence of noise in the mode shape data. Firstly, the paper presents a sequential curve fitting technique that reduces the effect of noise on the calculation process of the MSEDI, more effectively than the two commonly used curve fitting techniques; namely, polynomial and Fourier’s series. Secondly, a probability based Generalized Damage Localization Index (GDLI) is proposed as a viable improvement to the damage detection process. The study uses a validated ABAQUS finite-element model of a reinforced concrete beam to obtain mode shape data in the undamaged and damaged states. Noise is simulated by adding three levels of random noise (1%, 3%, and 5%) to the mode shape data. Results show that damage detection is enhanced with increased number of modes and samples used with the GDLI.
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The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.
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As a part of vital infrastructure and transportation network, bridge structures must function safely at all times. Bridges are designed to have a long life span. At any point in time, however, some bridges are aged. The ageing of bridge structures, given the rapidly growing demand of heavy and fast inter-city passages and continuous increase of freight transportation, would require diligence on bridge owners to ensure that the infrastructure is healthy at reasonable cost. In recent decades, a new technique, structural health monitoring (SHM), has emerged to meet this challenge. In this new engineering discipline, structural modal identification and damage detection have formed a vital component. Witnessed by an increasing number of publications is that the change in vibration characteristics is widely and deeply investigated to assess structural damage. Although a number of publications have addressed the feasibility of various methods through experimental verifications, few of them have focused on steel truss bridges. Finding a feasible vibration-based damage indicator for steel truss bridges and solving the difficulties in practical modal identification to support damage detection motivated this research project. This research was to derive an innovative method to assess structural damage in steel truss bridges. First, it proposed a new damage indicator that relies on optimising the correlation between theoretical and measured modal strain energy. The optimisation is powered by a newly proposed multilayer genetic algorithm. In addition, a selection criterion for damage-sensitive modes has been studied to achieve more efficient and accurate damage detection results. Second, in order to support the proposed damage indicator, the research studied the applications of two state-of-the-art modal identification techniques by considering some practical difficulties: the limited instrumentation, the influence of environmental noise, the difficulties in finite element model updating, and the data selection problem in the output-only modal identification methods. The numerical (by a planer truss model) and experimental (by a laboratory through truss bridge) verifications have proved the effectiveness and feasibility of the proposed damage detection scheme. The modal strain energy-based indicator was found to be sensitive to the damage in steel truss bridges with incomplete measurement. It has shown the damage indicator's potential in practical applications of steel truss bridges. Lastly, the achievement and limitation of this study, and lessons learnt from the modal analysis have been summarised.
Resumo:
Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.
Resumo:
The Black Rat (Rattus rattus), a global pest within the macadamia production industry, causes up to 30% crop damage in Australian orchards. During early stages of production in Australia, research demonstrated the importance of non crop adjacent habitats as significant in affecting the patterns of crop damage seen throughout orchards. Where once rodent damage was limited to the outside edges of orchard blocks, growers are now reporting finding crop damage throughout entire orchards. This study therefore aims to explore the spatial patterns of rodent distribution and damage now occurring in Australian macadamia orchards. We show that rodent damage and rodent distribution in these newer production regions differ from that shown in previous Australian research. Previous Australian research has shown damage patterns which were associated with the edges of orchard blocks however this study demonstrates a more widespread damage distribution. In the current study there is no relationship between rodent damage and the orchard edge. Arboreal rodent nests were identified within these newer orchard systems, suggesting rodents are residing within the tree component of the orchard system and not dependent on adjacent non-crop habitat for shelter. Results from this study confirm that rodents have modified their nesting and foraging behaviour in newer orchards systems in Australia. We suggest that this is a response of increased and prolonged availability of macadamia nuts in newer production regions enabling populations to be maintained throughout the year. Management strategies will require modification if control is to be achieved.
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Exercise-induced muscle damage is an important topic in exercise physiology. However several aspects of our understanding of how muscles respond to highly stressful exercise remain unclear In the first section of this review we address the evidence that exercise can cause muscle damage and inflammation in otherwise healthy human skeletal muscles. We approach this concept by comparing changes in muscle function (i.e., the force-generating capacity) with the degree of leucocyte accumulation in muscle following exercise. In the second section, we explore the cytokine response to 'muscle-damaging exercise', primarily eccentric exercise. We review the evidence for the notion that the degree of muscle damage is related to the magnitude of the cytokine response. In the third and final section, we look at the satellite cell response to a single bout of eccentric exercise, as well as the role of the cyclooxygenase enzymes (COX1 and 2). In summary, we propose that muscle damage as evaluated by changes in muscle function is related to leucocyte accumulation in the exercised muscles. 'Extreme' exercise protocols, encompassing unaccustomed maximal eccentric exercise across a large range of motion, generally inflict severe muscle damage, inflammation and prolonged recovery (> 1 week). By contrast, exercise resembling regular athletic training (resistance exercise and downhill running) typically causes mild muscle damage (myofibrillar disruptions) and full recovery normally occurs within a few days. Large variation in individual responses to a given exercise should, however be expected. The link between cytokine and satellite cell responses and exercise-induced muscle damage is not so clear The systemic cytokine response may be linked more closely to the metabolic demands of exercise rather than muscle damage. With the exception of IL-6, the sources of systemic cytokines following exercise remain unclear The satellite cell response to severe muscle damage is related to regeneration, whereas the biological significance of satellite cell proliferation after mild damage or non-damaging exercise remains uncertain. The COX enzymes regulate satellite cell activity, as demonstrated in animal models; however the roles of the COX enzymes in human skeletal muscle need further investigation. We suggest using the term 'muscle damage' with care. Comparisons between studies and individuals must consider changes in and recovery of muscle force-generating capacity.
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When wheels pass over insulated rail joints (IRJs) a vertical impact force is generated. The ability to measure the impact force is valuable as the force signature helps understand the behaviour of the IRJs, in particular their potential for failure. The impact forces are thought to be one of the main factors that cause damage to the IRJ and track components. Study of the deterioration mechanism helps finding new methods to improve the service life of IRJs in track. In this research, the strain-gage-based wheel load detector, for the first time, is employed to measure the wheel–rail contact-impact force at an IRJ in a heavy haul rail line. In this technique, the strain gages are installed within the IRJ assembly without disturbing the structural integrity of IRJ and arranged in a full wheatstone bridge to form a wheel load detector. The instrumented IRJ is first tested and calibrated in the lab and then installed in the field. For comparison purposes, a reference rail section is also instrumented with the same strain gage pattern as the IRJ. In this paper the measurement technique, the process of instrumentation, and tests as well as some typical data obtained from the field and the inferences are presented.
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Altered expression of the INT6 gene, encoding the e subunit of the translational initiation factor eIF3, occurs in human breast cancers, but how INT6 relates to carcinogenesis remains unestablished. Here, we show that INT6 is involved in the DNA damage response. INT6 was required for cell survival following γ-irradiation and G(2)-M checkpoint control. RNA interference-mediated silencing of INT6 reduced phosphorylation of the checkpoint kinases CHK1 and CHK2 after DNA damage. In addition, INT6 silencing prevented sustained accumulation of ataxia telangiectasia mutated (ATM) at DNA damage sites in cells treated with γ-radiation or the radiomimetic drug neocarzinostatin. Mechanistically, this result could be explained by interaction of INT6 with ATM, which together with INT6 was recruited to the sites of DNA damage. Finally, INT6 silencing also reduced ubiquitylation events that promote retention of repair proteins at DNA lesions. Accordingly, accumulation of the repair factor BRCA1 was defective in the absence of INT6. Our findings reveal unexpected and striking connections of INT6 with ATM and BRCA1 and suggest that the protective action of INT6 in the onset of breast cancers relies on its involvement in the DNA damage response.
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This paper develops and applies a multi-criteria procedure, incorporating changes in natural frequencies, modal flexibility and the modal strain energy, for damage detection in slab-on-girder bridges. The proposed procedure is first validated through experimental testing of a model bridge. Numerically simulated modal data obtained through finite element analyses are then used to evaluate the vibration parameters before and after damage and used as the indices for assessment of the state of structural health. The procedure is illustrated by its application to full scale slab-on-girder bridges under different damage scenarios involving single and multiple damages on the deck and girders.
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The resection of DNA double-strand breaks (DSBs) to generate ssDNA tails is a pivotal event in the cellular response to these breaks. In the two-step model of resection, primarily elucidated in yeast, initial resection by Mre11-CtIP is followed by extensive resection by two distinct pathways involving Exo1 or BLM/WRN-Dna2. However, resection pathways and their exact contributions in humans in vivo are not as clearly worked out as in yeast. Here, we examined the contribution of Exo1 to DNA end resection in humans in vivo in response to ionizing radiation (IR) and its relationship with other resection pathways (Mre11-CtIP or BLM/WRN). We find that Exo1 plays a predominant role in resection in human cells along with an alternate pathway dependent on WRN. While Mre11 and CtIP stimulate resection in human cells, they are not absolutely required for this process and Exo1 can function in resection even in the absence of Mre11-CtIP. Interestingly, the recruitment of Exo1 to DNA breaks appears to be inhibited by the NHEJ protein Ku80, and the higher level of resection that occurs upon siRNA-mediated depletion of Ku80 is dependent on Exo1. In addition, Exo1 may be regulated by 53BP1 and Brca1, and the restoration of resection in BRCA1-deficient cells upon depletion of 53BP1 is dependent on Exo1. Finally, we find that Exo1-mediated resection facilitates a transition from ATM- to ATR-mediated cell cycle checkpoint signaling. Our results identify Exo1 as a key mediator of DNA end resection and DSB repair and damage signaling decisions in human cells.
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Thin-sectioned samples mounted on glass slides with common petrographic epoxies cannot be easily removed (for subsequent ion-milling) by standard methods such as heating or dissolution in solvents. A method for the removal of such samples using a radio frequency (RF) generated oxygen plasma has been investigated for a number of typical petrographic and ceramic thin sections. Sample integrity and thickness were critical factors that determined the etching rate of adhesive and the survivability of the sample. Several tests were performed on a variety of materials in order to estimate possible heating or oxidation damage from the plasma. Temperatures in the plasma chamber remained below 138°C and weight changes in mineral powders etched for 76 hr were less than ±4%. A crystal of optical grade calcite showed no apparent surface damage after 48 hr of etching. Any damage from the oxygen plasma is apparently confined to the surface of the sample, and is removed during the ion-milling stage of transmission electron microscopy (TEM) sample preparation.