Adaptation planning for climate-resilient urban infrastructures

This paper analyzes the interdependency across two critical infrastructures of transportation and motor fueling supply chains, and investigates how vulnerability to climatic extremes in a fueling infrastructure hampers the resilience of a transportation system. The proposed model features both a bi-stage mathematical program and an extension to an ‘α-reliable mean-excess’ regret model. The former aspect allows decision makers to optimize the pre-disaster asset prepositioning against the maximum post-disaster system resilience. The latter aspect of the proposed model devalues the impact of ‘low-probability, high-cost’ sub-scenarios upon model results. The model reveals the reliance of post-disaster urban mobility on the interdependent critical infrastructure of motor fueling supply chains. The results also suggest how investment in the fueling infrastructure’s vulnerable elements protects urban mobility while the transportation network is stressed or under attack.     

Modeling the choice continuum: an integrated model of residential location,auto ownership,bicycle ownership,and commute tour mode choice decisions

The integrated modeling of land use and transportation choices involves analyzing a continuum of choices that characterize people’s lifestyles across temporal scales. This includes long-term choices such as residential and work location choices that affect land-use, medium-term choices such as vehicle ownership, and short-term choices such as travel mode choice that affect travel demand. Prior research in this area has been limited by the complexities associated with the development of integrated model systems that combine the long-, medium- and short-term choices into a unified analytical framework. This paper presents an integrated simultaneous multi-dimensional choice model of residential location, auto ownership, bicycle ownership, and commute tour mode choices using a mixed multidimensional choice modeling methodology. Model estimation results using the San Francisco Bay Area highlight a series of interdependencies among the multi-dimensional choice processes. The interdependencies include: (1) self-selection effects due to observed and unobserved factors, where households locate based on lifestyle and mobility preferences, (2) endogeneity effects, where any one choice dimension is not exogenous to another, but is endogenous to the system as a whole, (3) correlated error structures, where common unobserved factors significantly and simultaneously impact multiple choice dimensions, and (4) unobserved heterogeneity, where decision-makers show significant variation in sensitivity to explanatory variables due to unobserved factors. From a policy standpoint, to be able to forecast the “true” causal influence of activity-travel environment changes on residential location, auto/bicycle ownership, and commute mode choices, it is necessary to capture the above-identified interdependencies by jointly modeling the multiple choice dimensions in an integrated framework.     

Effects of increased awareness on choice of travel mode

This paper reports a field experiment with the purpose of studying the effects of increased awareness on travel mode choice. One hundred fifteen subjects were randomly assigned to an experimental and a control group. In the experimental group, a more deliberate choice of travel mode was induced and expected to result in a stronger relationship between attitude and behavior, a weaker relationship between habit and behavior, and a behavioral change among individuals with a strong habit. Attitude, habit, and behavior were measured in travel diaries and questionnaires. The results indicated no significant change in the relationship between attitude and behavior and no significant change in the relationship between habit and behavior. However, a temporally extended decrease in car use was observed in the experimental group. The effect was noted for individuals with a strong habit who reduced their car use but not for subjects with a weak habit.     

An assessment of models to estimate pedestrian demand based on the level of activity

This paper presents the development and assessment of models to estimate pedestrian demand based on the level of pedestrian activity (high and low). As activity varies by the time of the day, temporal variations were evaluated by considering different time periods. Data collected at 128 low and 48 high pedestrian activity signalized intersections (a total of 176 signalized intersections) in the City of Charlotte, North Carolina were used to develop and assess the models using stepwise regression analysis through backward elimination of independent variables (includes demographic, land use, and network characteristics). The use of different buffer widths (proximal area) to extract these characteristics was also evaluated. Results, in general, show that pedestrian demand varied by the level of activity, explanatory variables extracted by buffer width, and time of the day. The estimates from the models could be used in transportation planning (identify required pedestrian facilities, resource allocation), safety, and operational analyses. Copyright © 2010 John Wiley & Sons, Ltd.     

Analysis of high dynamic car manoeuvres using two types of lever-arm correction

As navigation algorithms using Kalman filters, fuzzy or adaptive algorithms, interacting multiple model (IMM) algorithms and other possible solutions combining data from several sensors, have been progressively used in the last decade, there has been little advance in developing a robust and accurate device available for car manufacturers. The most solutions fail in long-term reliability and/or use too generalized linearization models. This is why in this paper we have examined some high dynamic manoeuvres which are usually a part of automotive tests. Some major issues during these manoeuvres were identified and a modified Kalman filter solution is presented. The problem of positioning of an inertial device within a vehicle is addressed and a transformation of measured data to the centre of gravity (COG) or rotation point (RP) of the vehicle is introduced. We also propose a few methods to identify the start and the stop of a brake test and show distance difference between conventional and modified Kalman algorithm during driving in circles. Finally, a direct and indirect lever-arm correction is introduced and real road tests are made to present an improvement in outputs using one-device sensor setup.     

Grey-Fuzzy Taguchi approach for multi-objective optimization of performance and emission parameters of a single cylinder crdi engine coupled with EGR

The present study attempts to address the challenges of the multiobjective optimization problem of the BSFC-NOx-PM trade-off paradox of an existing diesel engine by harnessing the synergetic benefit of PM and BSFC reduction through CRDI operation and simultaneous NOx reduction by EGR application. Load, FIP and EGR were chosen as the input parameters while NOx, PM and BSFC were the response variables. In order to reduce the experimental effort, the Taguchi L₁₆ orthogonal array technique was employed to obtain the corresponding values of the response variables. The grey relational analysis coupled with fuzzy logic has been employed as the optimization routine. The optimal combination of the input parameters corresponding to the calibrated values of the response variables were obtained by employing the Grey-Fuzzy Grade and S-N ratio strategy as a performance index. The computed optimal combination so obtained were further validated through actual experimentation. EGR was found to be the most influencing factor in the present optimization endeavour. The study also established that the Grey-Fuzzy-Taguchi method was not only comparable but superior to the Grey-Taguchi method usually employed for such optimization studies.     

Investigation and analysis of high temperature corrosion and degradation of marine boiler combustion swirler

The present paper investigated and analyzed swirler material consisting of mild steel which was subjected to service for the period of one year in a 30 MW marine boiler. Due to the presence of high temperatures in the furnace coupled with the corrosive marine environment swirler material showed accelerated degradation and material wastage. An investigation into the feasibility of manufacturing the existing swirler with an alternate material or coating the swirler material with a thermal barrier coating was undertaken. Based on their properties and performance, SS 304 and SS 316 were proposed as the replacement materials for the swirler. The other alternative of coating the existing swirlers with a form thermal barrier coating to observe for any improvement in their performance at elevated temperatures was also tested. Stellite, which is a Ni-Co based coating, was carried out on the MS samples and the same were exposed to same temperatures mentioned above. The performance of the available options was evaluated with respect to the grain structure of the material, the hardness value of the materials and deterioration at elevated temperatures. Investigation showed the proposed materials/coatings like SS 304, SS 316 and Stellite coating revealed that SS 316 is the material best suited for high temperature application.