872 resultados para Wind damage


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Ultraviolet (UV) radiation potentially damages the skin, the immune system, and structures of the eye. A useful UV sun protection for the skin has been established. Since a remarkable body of evidence shows an association between UV radiation and damage to structures of the eye, eye protection is important, but a reliable and practical tool to assess and compare the UV-protective properties of lenses has been lacking. Among the general lay public, misconceptions on eye-sun protection have been identified. For example, sun protection is mainly ascribed to sunglasses, but less so to clear lenses. Skin malignancies in the periorbital region are frequent, but usual topical skin protection does not include the lids. Recent research utilized exact dosimetry and demonstrated relevant differences in UV burden to the eye and skin at a given ambient irradiation. Chronic UV effects on the cornea and lens are cumulative, so effective UV protection of the eyes is important for all age groups and should be used systematically. Protection of children's eyes is especially important, because UV transmittance is higher at a very young age, allowing higher levels of UV radiation to reach the crystalline lens and even the retina. Sunglasses as well as clear lenses (plano and prescription) effectively reduce transmittance of UV radiation. However, an important share of the UV burden to the eye is explained by back reflection of radiation from lenses to the eye. UV radiation incident from an angle of 135°-150° behind a lens wearer is reflected from the back side of lenses. The usual antireflective coatings considerably increase reflection of UV radiation. To provide reliable labeling of the protective potential of lenses, an eye-sun protection factor (E-SPF®) has been developed. It integrates UV transmission as well as UV reflectance of lenses. The E-SPF® compares well with established skin-sun protection factors and provides clear messages to eye health care providers and to lay consumers.

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This paper reports a series of experiments on patient JB, a man with memory difficulties following damage to the left frontal lobe. The primary characteristic of JB's recognition memory impairment is a high level of false recognition together with a normal hit rate. The hypothesis that JB's false recognition reflects an over-reliance on familiarity is considered, but discounted on the basis that the false alarm rate is not affected by increasing the similarity between distracters and targets, and remains high when nonword stimuli are used. It is suggested, instead, that JB relies on a poorly focused memory description, which lacks item-specific detail but contains more general, low-level properties of the target items-these properties being held by many distracter items as well. This deficit is considered to arise because of damage to frontally mediated control processes involved in the selection of elements for memory encoding. An encoding deficit is supported by the fact that JB's false recognition is significantly reduced by orienting instructions, and is eliminated when his remote memory is subjected to recognition testing. In contrast, it is shown that manipulations at the level of retrieval (e.g. restricting the number of "old" responses) have little effect on his false recognition.

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We consider damage spreading transitions in the framework of mode-coupling theory. This theory describes relaxation processes in glasses in the mean-field approximation which are known to be characterized by the presence of an exponentially large number of metastable states. For systems evolving under identical but arbitrarily correlated noises, we demonstrate that there exists a critical temperature T0 which separates two different dynamical regimes depending on whether damage spreads or not in the asymptotic long-time limit. This transition exists for generic noise correlations such that the zero damage solution is stable at high temperatures, being minimal for maximal noise correlations. Although this dynamical transition depends on the type of noise correlations, we show that the asymptotic damage has the good properties of a dynamical order parameter, such as (i) independence of the initial damage; (ii) independence of the class of initial condition; and (iii) stability of the transition in the presence of asymmetric interactions which violate detailed balance. For maximally correlated noises we suggest that damage spreading occurs due to the presence of a divergent number of saddle points (as well as metastable states) in the thermodynamic limit consequence of the ruggedness of the free-energy landscape which characterizes the glassy state. These results are then compared to extensive numerical simulations of a mean-field glass model (the Bernasconi model) with Monte Carlo heat-bath dynamics. The freedom of choosing arbitrary noise correlations for Langevin dynamics makes damage spreading an interesting tool to probe the ruggedness of the configurational landscape.

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Following a high wind event on January 24, 2006, at least five people claimed to have seen or felt the superstructure of the Saylorville Reservoir Bridge in central Iowa moving both vertically and laterally. Since that time, the Iowa Department of Transportation (DOT) contracted with the Bridge Engineering Center at Iowa State University to design and install a monitoring system capable of providing notification of the occurrence of subsequent high wind events. In subsequent years, a similar system was installed on the Red Rock Reservoir Bridge to provide the same wind monitoring capabilities and notifications to the Iowa DOT. The objectives of the system development and implementation are to notify personnel when the wind speed reaches a predetermined threshold such that the bridge can be closed for the safety of the public, correlate structural response with wind-induced response, and gather historical wind data at these structures for future assessments. This report describes the two monitoring systems, their components, upgrades, functionality, and limitations, and results from one year of wind data collection at both bridges.

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Following high winds on January 24, 2006, at least five people claimed to have seen or felt the superstructure of the Saylorville Reservoir Bridge in central Iowa moving both vertically and laterally. Since that time, the Iowa Department of Transportation (DOT) contracted with the Bridge Engineering Center at Iowa State University to design and install a monitoring system capable of providing notification of the occurrence of subsequent high winds. Although measures were put into place following the 2006 event at the Saylorville Reservoir Bridge, knowledge of the performance of this bridge during high wind events was incomplete. Therefore, the Saylorville Reservoir Bridge was outfitted with an information management system to investigate the structural performance of the structure and the potential for safety risks. In subsequent years, given the similarities between the Saylorville and Red Rock Reservoir bridges, a similar system was added to the Red Rock Reservoir Bridge southeast of Des Moines. The monitoring system developed and installed on these two bridges was designed to monitor the wind speed and direction at the bridge and, via a cellular modem, send a text message to Iowa DOT staff when wind speeds meet a predetermined threshold. The original intent was that, once the text message is received, the bridge entrances would be closed until wind speeds diminish to safe levels.

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This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

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In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.

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The 2011 Missouri River flooding caused significant damage to many geo-infrastructure systems including levees, bridge abutments/foundations, paved and unpaved roadways, culverts, and embankment slopes in western Iowa. The flooding resulted in closures of several interchanges along Interstate 29 and of more than 100 miles of secondary roads in western Iowa, causing severe inconvenience to residents and losses to local businesses. The main goals of this research project were to assist county and city engineers by deploying and using advanced technologies to rapidly assess the damage to geo-infrastructure and develop effective repair and mitigation strategies and solutions for use during future flood events in Iowa. The research team visited selected sites in western Iowa to conduct field reconnaissance, in situ testing on bridge abutment backfills that were affected by floods, flooded and non-flooded secondary roadways, and culverts. In situ testing was conducted shortly after the flood waters receded, and several months after flooding to evaluate recovery and performance. Tests included falling weight deflectometer, dynamic cone penetrometer, three-dimensional (3D) laser scanning, ground penetrating radar, and hand auger soil sampling. Field results indicated significant differences in roadway support characteristics between flooded and non-flooded areas. Support characteristics in some flooded areas recovered over time, while others did not. Voids were detected in culvert and bridge abutment backfill materials shortly after flooding and several months after flooding. A catalog of field assessment techniques and 20 potential repair/mitigation solutions are provided in this report. A flow chart relating the damages observed, assessment techniques, and potential repair/mitigation solutions is provided. These options are discussed for paved/unpaved roads, culverts, and bridge abutments, and are applicable for both primary and secondary roadways.