999 resultados para nanoscale metallic air-bridge


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Whole body cryotherapy (WBC) involves repeatedly exposing an individual, dressed in minimal clothing, to extremely cold air (–100 to –130°C) for a short period. One specific claim that is often made is that WBC is effective in treating exercise-induced muscle soreness and damage. However, our results suggest that two bouts of WBC were ineffective in improving recovery from eccentric exercise when administered 24 hours after eccentric exercise.

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Initial crack widely exists in the welded members of steel bridge induced by the welding procedure or by the fatigue damage crack initiation. The behavior of crack growth with a view to fatigue damage accumulation on the tip of cracks is discussed. Fatigue life of welded components with initial crack in bridges under traffic loading is investigated. Based on existing fatigue experiment results of welded members with initial crack and the fatigue experiment results of welded bridge members under constant stress cycles, the crack would keep semi-elliptical shape with variable ratio of a/c during the crack propagation. Based on the concept of continuum damage accumulated on the tip of fatigue cracks,the fatigue damage law suitable for steel bridge members under traffic loading is modified to consider the crack growth.The virtual crack growth method and the semi-elliptical crack shape assumption are proposed in this paper to deduce a new model of fatigue crack growth rate for welded bridge members under traffic loading. And the calculated method of the stress intensity factor necessary for evaluation of the fatigue life of welded bridge members with cracks is discussed.The proposed fatigue crack growth model is then applied to calculate the crack growth and the fatigue life of existing welded members with fatigue experimental results. The fatigue crack propagation computation results show that the ratio of crack depth to the half crack surface length a/c is variable during crack propagation process and the stress cycle increases with the increase of a0/c0 with certain a0/t0 .The calculated and measured fatigue lives are generally in good agreement,at some initial conditions of cracking, for welded members widely used in steel bridges.

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The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.

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Memoir excerpt

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Nitrate reduction with nanoscale zero-valent iron (NZVI) was reported as a potential technology to remove nitrate from nitrate-contaminated water. In this paper, nitrate reduction with NZVI prepared by hydrogen reduction of natural goethite (NZVI-N, -N represents natural goethite) and hydrothermal goethite (NZVI-H, -H represents hydrothermal goethite) was conducted. Besides, the effects of reaction time, nitrate concentration, iron-to-nitrate ratio on nitrate removal rate over NZVI-H and NZVI-N were investigated. To prove their excellent nitrate reduction capacities, NZVI-N and NZVI-H were compared with ordinary zero-valent iron (OZVI-N) through the static experiments. Based on all above investigations, the mechanism of nitrate reduction with NZVI-N was proposed. The result showed that reaction time, nitrate concentration, iron-to-nitrate ratio played an important role in nitrate reduction by NZVI-N and NZVI-H. Compared with OZVI, NZVI-N and NZVI-H showed little relationship with pH. And NZVI-N for nitrate composition offers a higher stability than NZVI-H because of the existence of Al-substitution. Furthermore, NZVI-N, prepared by hydrogen reduction of goethite, has higher activity for nitrate reduction and the products contain hydrogen, nitrogen, NH 4 +, a little nitrite, but no NOx, meanwhile NZVI-N was oxidized to Fe 2+. It is a relatively easy and cost-effective method for nitrate removal, so NZVI-N reducing nitrate has a great potential application in nitrate removal of groundwater. © 2012 Elsevier B.V.

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Unsteady numerical simulation of Rayleigh Benard convection heat transfer from a 2D channel is performed. The oscillatory behavior is attributed to recirculation of ascending and descending flows towards the core of the channel producing organized rolled motions. Variation of the parameters such as Reynolds number, channel outlet flow area and inclination of the channel are considered. Increasing Reynolds number (for a fixed Rayleigh number), delays the generation of vortices. The reduction in the outflow area leads to the later and the less vortex generation. As the time progresses, more vortices are generated, but the reinforced mean velocity does not let the eddies to enter the core of the channel. Therefore, they attach to the wall and reduce the heat transfer area. The inclination of the channel (both positive and negative) induces the generated vortices to get closer to each other and make an enlarged vortex.

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4D simulation, building information modeling, virtual construction, computer simulation and virtual prototyping are emerging topics in the building construction industry. These techniques not only relate to the buildings themselves, but can also be applied to other forms of construction, including bridges. Since bridge construction is a complex process involving multiple types of plant and equipment, applying such virtual methods benefits the understanding of all parties in construction practice. This paper describes the relationship between temporary platforms, plant and equipment resources and a proposed-built model in the construction planning and use of Virtual Prototyping Simulation (VPS) to implement different construction scenarios in order to help planners identify an optimal construction plan. A case study demonstrates the use of VPS integrated with temporary platform design and plant and equipment-resource allocation to generate different construction scenarios.

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The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

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Although ambient air pollution exposure has been linked with poor health in many parts of the world, no previous study has investigated the effect on morbidity in the city of Adelaide, South Australia. To explore the association between particulate matter (PM) and hospitalisations, including respiratory and cardiovascular admissions in Adelaide, South Australia. Methods: For the study period September 2001 to October 2007, daily counts of all-cause, cardiovascular and respiratory hospital admissions were collected, as well as daily air quality data including concentrations of particulates, ozone and nitrogen dioxide. Visibility codes for presentweather conditions identified dayswhen airborne dust or smoke was observed. The associations between PM and hospitalisations were estimated using timestratified case-crossover analyses controlling for covariates including temperature, relative humidity, other pollutants, day of the week and public holidays. Mean PM10 concentrations were higher in the warm season, whereas PM2.5 concentrations were higher in the cool season. Hospital admissions were associated with PM10 in the cool season and with PM2.5 in both seasons. No significant effect of PM on all-age respiratory admissions was detected, however cardiovascular admissions were associated with both PM2.5 and PM10 in the cool season with the highest effects for PM2.5 (4.48%, 95% CI: 0.74%, 8.36% increase per 10 μg/m3 increase in PM2.5). These findings suggest that despite the city's relatively low levels of air pollution, PMconcentrations are associated with increases in morbidity in Adelaide. Further studies are needed to investigate the sources of PM which may be contributing to the higher cool season effects.