具有惯性表面的两层流体的柯西-泊松问题(英文)

This paper is concerned with the generation of waves due to initial disturbances at the upper surface of a two-layer fluid, as the upper layer is covered by an inertial surface and the lower layer extends infinitely downwards. The inertial surface is composed of thin but uniform distribution of non-interacting material. In the mathematical analysis, the Fourier and Laplace transform techniques have been utilized to obtain the depressions of the inertial surface and the interface in the form of infinite integrals. For initial disturbances concentrated at a point, the inertial surface depression and the interface depression are evaluated asymptotically for large time and distance by using the method of stationary phase. They are also depicted graphically for two types of initial disturbances and appropriate conclusions are made.     

Comprehensive Review of the Maritime Safety Regimes: Present Status and Recommendations for Improvements

Abstract

This article presents a comprehensive review of the maritime safety regimes and provides recommendations on how to improve the system. The results show a complex legal framework which generates a high amount of inspections and overlapping of inspection areas where no cross‐recognition is established by the various stakeholders. While the safety system seems to be successful in eliminating substandard vessels and while average insurance claims costs are substantially lower for inspected vessels than non‐inspected vessels, the results indicate that the economic conditions of the shipping market also have an effect on safety quality besides the frequency of inspections. No significant differences can be found between industry inspections and port state control inspections with respect to decreasing the probability of casualty. The system could be made more effective by combining data sources on inspections and using them respectively to improve risk profiling and to decrease the frequency of inspections performed on ship types such as tankers. The results further indicate a lack of proper implementation of the International Safety Management Code (ISM code) and conventions with reference to working and living conditions of crew (ILO 147). A revision of the ISM code and more emphasis on enforcement of ILO 147 could further enhance the level of safety at sea. The authors would like to thank several inspection regimes for their cooperation in providing inspection data and in allowing the observation of surveys and inspections on 26 vessels. In addition, the authors would like to acknowledge the data providers for the casualty data, Clarksons for the economic data as well as two P&I Clubs in making data on insurance claims available.     

A multinomial logit car use model for a megacity of the developing world: Istanbul

The increase in motor vehicle use is one of the important factors that cause traffic congestion, especially in megacities. Thus, the reasons behind this increase require serious attention. This paper offers an analysis of this kind, for a megacity from the developing world, Istanbul. A stratified multinomial logit model accounting for the availability of a second vehicle in the household is estimated for a sample drawn from a questionnaire to gather information of actual car use in Istanbul. This estimation is only possible through a unique data generation process that converts actual preferences into a choice study setting. In addition, a simulation study, generally utilized in the analyses of discrimination between certain layers of society, and a scenario analysis related to changes in income are also included in the paper for a better understanding of the nature of the topic. The results show that the behavior of households with a second vehicle available and not available varies significantly due to household, individual and professional-related characteristics.     

Urea-SCR system optimization with various combinations of mixer types and decomposition pipe lengths

The demand for NO_x after-treatment system has increased dramatically due to the stricter NO_x emission regulations for diesel vehicles. The urea-SCR system is one of the NO_x after-treatment methods found to be quite effective to meet the regulation requirement enforced by various authorities including the Euro-6. In order to develop an effective urea-SCR system, it is critical to establish an even distribution of reductant over the catalyst surface since this favorable distribution can increase reduction reaction and in turn, improve NO_x conversion efficiencies. In the current study, a number of design variations of the urea-SCR system which included two mixer types and three decomposition pipe lengths, were evaluated systematically using CFD analysis and experimental measurements. The purpose of the CFD analysis was to estimate the distribution of reductant within the urea-SCR system with a specific configuration and the purpose of the engine emission test was to measure the amount of NO_x reduction, respectively. The results from the systematic analysis revealed the relation between the reductant distribution over the SCR and the performance of the NO_x reduction.     

Methodology for bus structure torsion stiffness and natural vibration frequency prediction based on a dimensional analysis approach

Engineering bus design requires testing of bus structures prototypes in order to guarantee a certain level of strength and an appropriate static and dynamic behavior of the bus superstructure when exposed to road loads. However, experimental testing of real bus structures is very expensive as it requires expensive resources and space. If testing is done on a scale bus model the previous required expenses are considerably reduced. Therefore, a novel methodology based on dimensional analysis applied to bus structure prediction to evaluate the bus structure static and dynamic performance is proposed. The static performance is evaluated attending to torsion stiffness and the dynamic in terms of the natural vibration frequencies and rollover threshold. A scale bus has been manufactured and dimensionless parameters have been defined in order to project the results obtained in the scale bus model to a larger model. Validation of the proposed methodology has been carried out under experimental and finite element analysis.     

A fuzzy stochastic approach to the multicriteria selection of an aircraft for regional chartering

This article deals with the problem of decision support for the selection of an aircraft. This is a problem faced by an airline company that is investing in regional charter flights in Brazil. The company belongs to an economic group whose core business is logistics. The problem has eight alternatives to be evaluated under 11 different criteria, whose measurements can be exact, stochastic, or fuzzy. The technique chosen for analyzing and then finding a solution to the problem is the multicriteria decision aiding method named NAIADE (Novel Approach to Imprecise Assessment and Decision Environments). The method used allows tackling the problems by working with quantitative as well as qualitative criteria under uncertainty and imprecision. Another considerable advantage of NAIADE over other multicriteria methods relies in its characteristics of not requiring a prior definition of the weights by the decision maker. As a conclusion, it can be said that the use of NAIADE provided for consistent results to that aircraft selection problem. Copyright © 2012 John Wiley & Sons, Ltd.     

The impact of weather conditions on bikeshare trips in Washington,DC

Bicycle usage can be affected by colder weather, precipitation, and excessive heat. The research presented here analyzes the effect of weather on the use of the Washington, DC, bikeshare system, exploiting a dataset of all trips made on the system. Hourly weather data, including temperature, rainfall, snow, wind, fog, and humidity levels are linked to hourly usage data. Statistical models linking both number of users and duration of use are estimated. Further, we evaluate trips from bikeshare stations within one quarter mile of Metro (subway) stations at times when Metro is operating. This allows us to determine whether Metro serves as a back-up option when weather conditions are unfavorable for bicycling. Results show that cold temperatures, rain, and high humidity levels reduce both the likelihood of using bikeshare and the duration of trips. Trips taken from bikeshare stations proximate to Metro stations are affected more by rain than trips not proximate to Metro stations and less likely when it is dark. This information is useful for understanding bicycling behavior and also for those planning bikeshare systems in other cities.     

Prediction of wave parameters by using fuzzy inference system and the parametric models along the south coasts of the Black Sea

Forecasting of sea-state characteristics has a great importance in coastal and ocean engineering studies. Therefore, the purpose of this study was to investigate performances of Adaptive-Network-Based Fuzzy Inference System (ANFIS) and several parametric methods in the Black Sea. For this purpose, different fuzzy models with different input combinations were developed for two different wind data sources (TSMS and ECMWF) at two offshore buoy stations. It also aimed to apply several approaches to event-based data sets for wave predictions. Generally, in literature the tendency is to use time series data for wave predictions. In this kind of prediction approach, lagged time series data are taken as inputs and current or future variables are taken as output. In this study, event-based data for each independent storm were extracted from time series data. Simultaneous or concurrent data of wind speed, blowing duration, fetch length and wave characteristics were detected for each single storm. These event data were then used to set up models. The hindcast results were validated with significant wave height and mean wave period data recorded in Hopa and Sinop buoy stations. The performance of developed fuzzy models were also compared with that of four different parametric methods (Wilson, SPM, Jonswap, and CEM methods) applied for two wind data sources at both buoy stations. Finally, it was determined that in the prediction of both wave parameters (H _s and T _z) the ANFIS models (R = 0.66, squared correlation coefficient, and MAE = 0.37 m, mean absolute error, for the best model in prediction of H _s) were more accurate than the parametric methods (R = 0.63 and MAE = 0.75 m for the best model in prediction of H _s).