A box model for North-East Atlantic coastal waters compared with radioactive tracers

A box model for the estimation of doses to members of the public from discharges of radioactivity into North-East Atlantic coastal waters has been used to predict annual means of radionuclide seawater concentrations which have been compared with measured data of tracer radionuclides, ¹³⁷Cs, ⁹⁹Tc and ¹²⁵Sb. Discharges of these radionuclides into the sea from the nuclear reprocessing plants Sellafield in the UK and La Hague in France have been used as input to the model. Fallout of ¹³⁷Cs from atmospheric nuclear weapons tests and fallout of ¹³⁷Cs from the Chernobyl accident into the Baltic Sea have been taken into account. A large proportion of the measured data was collected during the CEC MAST-900052 project which is concerned with the utilization of radionuclides as tracers for water movements. The data cover the time period 1972–1992. A comparison between predicted and measured concentrations of radionuclides in seawater indicated the need to improve the model with respect to mixing conditions in the English Channel and water transport from the North Sea to the Baltic Sea via the Skagerrak, the Kattegat and the Belt Sea. Improvements were made using the data for ¹³⁷Cs and ⁹⁹Tc and involved adjustments of the mixing conditions (water exchange rates) between adjacent water boxes while keeping the net advective water fluxes of the model unaltered. The results of the modified version of the model have been compared with observed values. The comparison shows a somewhat better agreement for ¹³⁷Cs and ¹²⁵Sb than for ⁹⁹Tc which is believed to be due to the lower reliability of the ⁹⁹Tc discharge data from Sellafield in 1978. An analysis of the predicted-to-observed seawater concentrations indicates an overall predictive accuracy of the model of 0.9 corresponding to a 10% underestimation and a predictive precision of about a factor of 2.5 at a confidence level of 95%. The ¹²⁵Sb data, which are independent of the tuning of the model, support the general conclusions about the model predictions of radionuclide concentrations in seawater.     

An inequality between two speed averages

In this note we invoke Schwartz's inequality to relate two speed averages.     

Performance indicator analysis: A management tool for the improvement of bus transit operation in Bangkok

This paper intends to demonstrate that the performance indicator analysis technique can be successfully used as a diagnostic tool to identify operational inefficiency and ineffectiveness at the route level of transit operation. The technique has been applied on 14 bus routes of Bangkok Mass Transit Authority to reveal the inter-route differences in operational efficiency and effectiveness. Twenty performance indicators relating to costs of services, fuel consumption, staff ratio, crew productivity, fleet utilization, service output per bus, daily revenues, etc., were selected to represent the resource efficiency, resource effectiveness and service effectiveness of the bus system. Results of the analyses revealed that considerable variations existed across the routes against many of these 20 selected indicators. These included variations in terms of labor and capacity utilization, maintenance expenditure, etc., many of which can be improved through suitable managerial measures. Based on these findings, specific recommendations have been made for improvement in the deficient areas that are considered to be within the operator domain. These indicators also provide a basis for comparison over time, with other operators and standards. A ranking scale was also developed to determine the over all attractiveness of the routes.     

Commuting trips within tours: how is commuting related to land use?

Studies that model the effects of land use on commuting generally use a trip-based approach or a more aggregated individual-based approach: i.e. commuting is conceptualized in terms of modal choice, distance and time per single trip, or in terms of daily commuting distance or time. However, people try to schedule activities in a daily pattern and, thus, consider tours instead of trips. Data from the 2000 to 2001 Travel Behaviour Survey in Ghent (Belgium) illustrate that car use and commuting times significantly differ between commuting trips within work-only tours and more complex tours. Therefore, this paper considers trip-related decisions simultaneously with tour-related decisions. A multiple group structural equation model (SEM) confirmed that the relationship between land use and commuting differs between work-only tours and more complex tours. Trips should be considered within tours in order to correctly understand the effect of land use scenarios such as densifying on commuting. Moreover, the use of multiple group SEM enabled us to address the issue of the complex nature of commuting. Due to interactions between various explanatory variables, land use patterns do not always have the presumed effect on commuting. Land use policy can successfully influence commuting, but only if it simultaneously accounts for the effects on car availability, car use, commuting distance and commuting time.     

Bicycle commuting in Melbourne during the 2000s energy crisis: A semiparametric analysis of intraday volumes

Cycling is attracting renewed attention as a mode of transport in western urban environments, yet the determinants of usage are poorly understood. In this paper we investigate some of these using intraday bicycle volumes collected via induction loops located at ten bike paths in the city of Melbourne, Australia, between December 2005 and June 2008. The data are hourly counts at each location, with temporal and spatial disaggregation allowing for the impact of meteorology to be measured accurately for the first time. Moreover, during this period petrol prices varied dramatically and the data also provide a unique opportunity to assess the cross-price elasticity of demand for cycling. Over-dispersed Poisson regression models are used to model volumes at each location and at each hour of the day. Seasonality and the impact of weather conditions are modelled as semiparametric and estimated using recently developed multivariate penalized spline methodology. Unlike previous studies that use aggregate data, the empirical results show a substantial meteorological and seasonal component to usage. They also suggest there was substitution into cycling as a mode of transport in response to increases in petrol prices, particularly during peak commuting periods and by commuters originating in wealthy and inner city neighbourhoods. Last, we extend the approach to a multivariate longitudinal count data model using a Gaussian copula estimated by Bayesian data augmentation. We find first order serial dependence in the hourly volumes and a ‘return trip’ effect in daily bicycle commutes.     

A basic mathematical model for evacuation problems in urban areas

Real life situations like floods, hurricanes or chemical accidents may cause the evacuation of a certain area to rescue the affected population. To enable a fast and a safe evacuation a basic mixed-integer evacuation model has been developed that provides a reorganization of the traffic routing of a certain area for the case of an evacuation. This basic problem of evacuation minimizes the evacuation-time while prohibiting conflicts within intersections. Our evacuation model is a dynamic network flow problem with additional variables for the number and direction of used lanes and with additional complicating constraints.Because of the size of the time-expanded network, the computational effort required by standard software is already very high for tiny instances. To deal with realistic instances we propose a heuristic approach.     

Combustion phase detection algorithm for four-cylinder controlled autoignition engines using in-cylinder pressure information

For several decades, the primary goal of the automotive industry has been to reduce harmful emissions and improve fuel economy. Gasoline engines are clean and powerful propulsion systems, but have poorer fuel economy than that of diesel engines. However, due to the development of new technologies such as variable valve timing and lift and direct gasoline injection, controlled autoignition (CAI) combustion can be realized. CAI engines combine the advantages of cleaner emissions and lower fuel consumption than conventional spark-ignition gasoline engines. In this study, a cylinder-pressure-based combustion phase detection method for CAI combustion is proposed. This method utilizes a normalized difference pressure (NDP), which is defined as the normalized pressure difference between the firing and motoring in-cylinder pressures. The proposed method was developed and validated with steady-state experimental data from an inline 4 cylinder, 2 L gasoline direct injection (GDI) CAI engine. Because the calculations in the NDP method are faster and simpler than in the conventional combustion phase detection method in CAI engines, this method can be embedded in a real-time controller. Furthermore, the proposed method displayed good accuracy in detecting the combustion phase and thus stabilized CAI combustion. Finally, the detailed experimental results are presented.     

Measurement of the disc-pad friction coefficient for mechanical brakes using direct and indirect methods

It is necessary to guarantee the proper brake force to stop a train safely in a limited distance and o adjust its speed. Currently, most trains are run by electrical power and have a combined electrical and mechanical (friction) braking system. The mechanical brake force is determined by many parameters, such as the friction coefficient of the brake disc and pad, the pressure in the brake cylinder, the brake cylinder’s cross sectional area and the brake linkage ratio. In general, the friction coefficient data of the brake disc and pad have been taken through a dynamo-test in a laboratory, but these data might not be well matched with real data under operating conditions because of the difference in data acquisition conditions. The present study examined two methodologies that can measure the friction coefficient of the brake pad and disc based on a train’s real operating conditions. The first method was the direct method, which measured the brake force and clamping force applied on the mechanical brake by using strain gauges installed on the brake to calculate the friction coefficient. The second was an indirect method that obtained the friction coefficient by using the weight of the train and the equivalent brake force. Those variables were calculated from the longitudinal dynamic characteristics, such as resistance to motion, gradient resistance and curved resistance. These two methodologies were used to obtain the disc-pad friction coefficient for the mechanical brakes of a Korean high-speed train (HSR350x).     

Capacity estimation of torque converters with piston holes using the response surface method and an artificial neural network

In new slim torque converters, lock-up clutches are used to provide high fuel efficiency at low speed. However, the slimness of the converters causes difficulty in heat dissipation, which may damage the friction material and shorten its life span. A cooling hole in the lock-up piston reduces the heat but also reduces the torque because oil flows through the hole due to the pressure difference between the two faces of the piston. In the early stages of the development of this type of torque converter, designers must consider the minimum flow rate required to cool the friction material and the minimum torque capacity required to transmit the engine torque. This research explored two methods of estimating these parameters. In the first method, an estimation equation was derived by combining the response surface method with physical properties such as the centrifugal force, a sudden expansion, a sudden contraction, and the steady flow energy equation. The second method involved the use of an artificial neural network. The feasibility of the estimates based on statistics and on the artificial neural network were confirmed in the design stage by comparing experimental and estimated data. An estimation program was created using the C#.Net language and has been used for actual torque converter designs by the Korea Powertrain Company.