Multi-response optimization of diesel engine performance parameters using thumba biodiesel-diesel blends by applying the Taguchi method and grey relational analysis

This paper presents an experimental study that involves an application of the Taguchi method and grey relational analysis to determine the optimum factor level to obtain optimum multiple-performance characteristics of a diesel engine run with different low-percentage thumba biodiesel-diesel blends. Four factors, namely, low-percentage thumba biodiesel-diesel blend, compression ratio, nozzle opening pressure and injection timing were each considered at three levels. An L₉ orthogonal array was used to collect data for various engine performance- and emission-related responses under different engine loads. The signal-to-noise (S/N) ratio and grey relational analysis were used for data analysis. The results of the study revealed that the combination of a blend consisting of 30% thumba biodiesel (B30), a compression ratio of 14, a nozzle opening pressure of 250 bar and an injection timing of 20° produces maximum multiple performance of a diesel engine with minimum multiple emissions from the engine.     

Numerical and experimental investigation of lubricating oil flow in a gerotor pump

Gerotor pumps are widely used in the automotive industry for engine oil lubrication, due to their high volumetric efficiency and smooth pumping action. In many cases, the lubricating oil from the sump is mixed with contaminants, such as dust and tiny solid particles, or becomes thickened, due to aging. These problems will lead to critical situations, such as increased noise, enhanced wear and erosion, and poor lubrication of the engine. These critical situations were studied by conducting a detailed CFD integrated investigation on a gerotor pump’s performance at different operating conditions in three phases, and the results are presented in this paper. In first phase, a CFD model of a gerotor pump was developed with a dynamic mesh for the rotary movement of both the inner and outer rotors. The effects on pump flow rate of important parameters, such as rotor speed, fluid viscosity and number of ports, were simulated using non-contaminated oil at room temperature and an elevated temperature of 140oC. The relationship between flow rate and pressure at different rotor speeds was predicted and validated with test data for further parametric study. The pressure ripples at different time steps were measured at different angular positions of the rotors to examine the model accuracy. It was found that the flow rate increased and pressure pulsation, as well as flow recirculation, was reduced when ports were added to the cover plate. A suction pipe with a strainer was added for the second phase to capture the undesired changes in flow behavior, such as cavitation, which is caused by negative suction at the inlet region of pump. A suitable size for the inlet suction pipe for this pump was chosen after performing tests to characterize the flow behavior with single and double ports. Next, the relationship between pressure drop and strainer porosity was determined using different porosity values for the strainers. In the final phase, oil with different concentrations of solids was simulated to measure the effect of solid particles on flow rates and pressure losses. It was observed that the intensity of the recirculation was reduced at the suction end at the higher concentration of 0.04%, due to particle inertial effects. It was also found that particle size distribution affected the overall efficiency and pressure head of the pump.     

Predictions of porpoising inception for planing vessels

The inception of porpoising is theoretically predicted for planing vessels. Two different approaches are presented. First, a linear stability analysis is applied to find the porpoising limits while the hydrodynamic coefficients, i.e. added mass and damping coefficients, are determined by either a simplified method or a numerical method. Another approach is to seek the porpoising limits by performing nonlinear time domain simulations. Either the simplified method or the numerical method is used in the simulations. In the numerical method, a 2D+t theory together with a boundary element method is employed. The trim angle limits for porpoising are determined by changing the longitudinal position of the centre of gravity (COG) of the vessel and keeping the forward speed constant. The predicted porpoising limits are compared with Day and Haag’s (Planing boat porpoising, Thesis, Webb Institute of Naval Architecture, 1952) experimental results. The influences of parameters such as the load coefficient, the vertical position of COG and the radius of gyration of the ship are investigated by varying those parameters in the linear stability analysis. In the nonlinear time-domain simulations, by trying different longitudinal position of COG, one can find the critical trim angle when the porpoising commences. The obtained trim limits agree generally with those predicted by the linear stability analysis. Bounded oscillations for the unstable cases near the critical trim angle can be seen in the time-domain simulations due to the nonlinear effects.     

Can rural older drivers meet their needs without a car? Stated adaptation responses from a GPS travel diary survey

Rural seniors are highly dependent on their automobile to meet their trip making needs, yet the effects of aging can make access to the vehicle difficult or impossible over time. The anticipated growth in the older person population, in concert with limited travel data available to support rural transportation planning in Canada suggests a disconnect between what rural older people may require for transportation and the availability of formal alternatives. Many will seek informal alternatives to driving, such as depending on friends and family, to meet their travel needs, but the degree is not well understood in the context of their actual vehicle usage and stated ability to adapt. This paper draws from a Global Positioning System (GPS)-based multi-day travel diary survey of a convenience sample of 60 rural older drivers (29 men, 31 women, average age of 69.6 years) from New Brunswick, Canada. Participants would rely on “friends and family” for 52% of all trips they undertook as driver in the survey, “walk or bike” for 14% of trips, and “not take the trip” in 34% of trips if they did not have access to a vehicle. The formal option of “Transit” was not selected as a viable alternative by any participant for any trip. “Medical trips”, “Shopping” and “Personal Errands” were the least discretionary of all trip types, yet the most difficult for participants to find alternate arrangements. This suggests the need to explore different models of service delivery, such as a community-supported, member-based rural shuttle service with volunteer and paid drivers that build on informal social networks and can provide service when friends and family are unavailable.     

Accounting for inertia in modal choices: some new evidence using a RP/SP dataset

Inertia is related with effect that experiences in previous periods may have on the current choice. In particular, it has to do with the tendency to stick with the past choice even when another alternative becomes more appealing. As new situations force individuals to rethink about their choices new preferences may be formed. Thus a learning process begins that relaxes the effect of inertia in the current choice. In this paper we use a mixed dataset of revealed preference (RP)-stated preference (SP) to study the effect of inertia between RP and SP observations and to study if the inertia effect is stable along the SP experiments. Inertia has been studied more extensively with panel datasets, but few investigations have used RP/SP datasets. In this paper we extend previous work in several ways. We test and compare several ways of measuring inertia, including measures that have been proposed for both short and long RP panel datasets. We also explore new measures of inertia to test for the effect of “learning” (in the sense of acquiring experience or getting more familiar with) along the SP experiment and we disentangle this effect from the pure inertia effect. A mixed logit model is used that allows us to account for both systematic and random taste variations in the inertia effect and for correlations among RP and SP observations. Finally we explore the relation between the utility specification (especially in the SP dataset) and the role of inertia in explaining current choices.     

Long-term behavior of particulate matters at urban roadside and background locations in Seoul,Korea

The concentrations of particulate matter, PM_2.5, PM₁₀, and TSP at an urban roadside and an urban background station are analyzed. Data collected over a 10 year period are analyzed. The concentrations of the particulates measured at the urban site are systematically larger than at the background station. The mean PM values at the former also exhibit a slight fall over the decade unlike those at the background station. Overall, the particulate matters at both locations are in an intermediate range of global level, e.g., approximately two times lower than those in other Asian regions but higher than in Europe.     

Analysis of within-household effects and between-household differences in maintenance activity allocation

This paper investigates the allocation of household individuals to out-of-home maintenance activities using the rich activity-travel diary data from the San Francisco Bay Area. Two inter-related decisions are considered in this context: (i) whether the given activity episode is performed individually (solo) or jointly, and (ii) the person who participates in the activity, if it is a solo activity. To account for the conditional nature of the solo activity person selection, a nested mixed logit modeling framework is proposed and implemented to jointly analyze person allocation for all maintenance activities performed by a household on a given day. The model is used to investigate within-household effects and between-household differences. The proposed model relaxes some important restrictions in person allocation models by accounting for various sources of correlations and relaxing the assumption of constant variance across households. The proposed model is used to analyze the differences in person allocation between different types of households. The results indicate that life-cycle and household role, income, gender, employment status, and several types of constraints (activities including cost, time-availability, vehicle-availability, coordination constraints, and child-care obligations) affect person allocation decisions in the context of maintenance activities. The empirical results indicate the presence of various sources of correlations across persons, over activities, and within-household that are significant. In addition, the data also provides evidence that the unobserved variances in person selection utilities are not constant across households. A better understanding of these within-household interactions and between-household differences may be used in activity-based simulation models and to develop more effective and focused demand management measures.     

Generating complete all-day activity plans with genetic algorithms

Activity-based demand generation contructs complete all-day activity plans for each member of a population, and derives transportation demand from the fact that consecutive activities at different locations need to be connected by travel. Besides many other advantages, activity-based demand generation also fits well into the paradigm of multi-agent simulation, where each traveler is kept as an individual throughout the whole modeling process. In this paper, we present a new approach to the problem, which uses genetic algorithms (GA). Our GA keeps, for each member of the population, several instances of possible all-day activity plans in memory. Those plans are modified by mutation and crossover, while bad instances are eventually discarded. Any GA needs a fitness function to evaluate the performance of each instance. For all-day activity plans, it makes sense to use a utility function to obtain such a fitness. In consequence, a significant part of the paper is spent discussing such a utility function. In addition, the paper shows the performance of the algorithm to a few selected problems, including very busy and rather non-busy days.     

The rational locator reexamined: Are travel times still stable?

The rational locator hypothesis posits that individuals can, if they choose, maintain approximately steady journey-to-work travel times by adjusting their home and workplace. This hypothesis was coupled with the observation of long-term stability in drive alone journey-to-work times in metropolitan Washington (those times were unchanged from 1957 through 1968 to 1988). Despite the increase of average commuting distance and congestion, trip duration remained constant or even declined when controlling for travel purpose and travel mode because of shifting a share of traffic from slow urban routes to faster suburban routes. This observation has significance, as it is important to know for travel demand analysis if there is an underlying budget, or even a regularity, as this helps us determine whether our forecasts are reasonable. To re-test the underlying rationale for the hypothesis that travel times are stable, intra-metropolitan comparisons of travel times are made using Washington DC data from 1968, 1988, and 1994, and Twin Cities data from 1990 and 2000. The results depend upon geography. For the larger Washington DC region, keeping the same geography shows little change in commute times, but using the larger 1994 area suggests an increase in commute times. However, the Twin Cities, starting from a much shorter commute time, shows a marked increase over the decade, using either the smaller or the larger geography. Despite the remarkable continuing observation of stability in drive alone commuting times in metropolitan Washington, we reject the theory of personal commuting budgets, as we find that not only are commuting times not generally stable over time at the intra-metropolitan area, but that commuting time clearly depends on metropolitan spatial structure.