The towed undulating vehicle (TUV), named SARAGO, was used for two fine-scale surveys between the Italian and the Sardinian coasts during the Astraea 2 cruise (6-7 and 26-27 September 1995), studying the deep chlorophyll maximum distribution. SARAGO sections identify a sub-surface doming with higher chlorophyll a and primary production concentrations in the upwelling area of a cyclonic gyre region, detected by sea-surface temperature images. In the first section, the cyclone presents a double doming, in density and salinity, with shallower and concentrated patches of chlorophyll a for about 2 miles. Twenty days later, the second section shows that the gyre changes shape and extension, showing a single doming with higher primary production and chlorophyll a concentrations, distributed over a large area of about 40 nautical miles. SARAGO allows analysis of this high-variability phenomenon (cyclonic gyre) and allows concentrated patches (2 nm) to be identified, thus proving the importance of TUVs in the study of mesoscale processes. 相似文献
This paper compares the life cycle energy use of a cast-aluminum, rear liftgate inner and a conventional, stamped steel liftgate inner used in a minivan. Using the best available aggregate life cycle inventory data and a simple spreadsheet-level analysis, energy comparisons were made at both the single-vehicle and vehicle-fleet levels. Since the product manufacture and use are distributed over long periods of time that, in a fleet, are not simple linear combinations of single product life cycles. Thus, it is all the products in use over a period of time, rather than a single product, that are more appropriate for the life cycle analysis. Using a set of consistent data, analyses also examine sensitivity to the level of analysis and the assumptions to determine the most favorable materials with respect to life cycle energy benefits.As expected, life cycle energy impacts of aluminum are lower than steel at a single-vehicle level – energy savings are determined to be 1.8 GJ/vehicle. Most energy savings occur at the vehicle operation phase due to improved fuel economy from lightweighting. The energy benefits are realized only very close to the average vehicle life of 14 years. With the incremental growth of the vehicle fleet, it takes longer – about 21 years – for aluminum to achieve life cycle equivalence with steel. The number of years aluminum needs to achieve equivalence with steel was found to be quite sensitive to aluminum manufacturing energy and fuel economy. As the steel industry races to compete with other materials for automotive lightweighting, a systems approach, instead of part-to-part comparison, is more appropriate in the determination of viability of aluminum substitution from an energy perspective. 相似文献
Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.
Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).
Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.
Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy. 相似文献