Shear-stress controlled dynamics of nematic complex fluids

Based on a mesoscopic theory we investigate the non-equilibrium dynamics of a sheared nematic liquid, with the control parameter being the shear stress $\sigma_{\mathrm{xy}}$ (rather than the usual shear rate, $\dot\gamma$). To this end we supplement the equations of motion for the orientational order parameters by an equation for $\dot\gamma$, which then becomes time-dependent. Shearing the system from an isotropic state, the stress- controlled flow properties turn out to be essentially identical to those at fixed $\dot\gamma$. Pronounced differences when the equilibrium state is nematic. Here, shearing at controlled $\dot\gamma$ yields several non-equilibrium transitions between different dynamic states, including chaotic regimes. The corresponding stress-controlled system has only one transition from a regular periodic into a stationary (shear-aligned) state. The position of this transition in the $\sigma_{\mathrm{xy}}$-$\dot\gamma$ plane turns out to be tunable by the delay time entering our control scheme for $\sigma_{\mathrm{xy}}$. Moreover, a sudden change of the control method can {\it stabilize} the chaotic states appearing at fixed $\dot\gamma$.Comment: 10 pages, 11 figure

Mixed logit modelling of airport choice in multi-airport regions

This paper presents an analysis of the choice of airport by air travellers departing from the San Francisco Bay (SF-B) area. The analysis uses the mixed multinomial logit model, which allows for a random distribution of tastes across decision makers. To our knowledge, this is the first application using this model form in the analysis of airport choice. The results indicate that there is significant heterogeneity in tastes, especially with respect to the sensitivity to access time, characterised by deterministic variations between groups of travellers (business/leisure, residents/visitors) as well as random variations within groups of travellers. The analysis reinforces earlier findings showing that business travellers are far less sensitive to fare increases than leisure travellers, and are willing to pay a higher price for decreases in access time (and generally also increases in frequency) than is the case for leisure travellers. Finally, the results show that the random variation between business travellers in terms of sensitivity to access time is more pronounced than that between leisure travellers, as is the case for visitors when compared to residents

Exploring the potential for cross-nesting structures in airport-choice analysis: A case-study of the Greater London area

The analysis of air-passengers’ choices of departure airport in multi-airport regions is a crucial component of transportation planning in many large metropolitan areas, and has been the topic of an increasing number of studies over recent years. In this paper, we advance the state of the art of modelling in this area of research by making use of a Cross-Nested Logit (CNL) structure that allows for the joint representation of inter-alternative correlation along the three choice dimensions of airport, airline and access-mode. The analysis uses data collected in the Greater London area, which arguably has the highest levels of inter-airport competition of any multi-airport region; the authors of this paper are not aware of any previous effort to jointly analyse the choice of airport, airline and access-mode in this area. The results of the analysis reveal significant influences on passenger behaviour by access-time, access-cost, flight-frequency and flight-time. A structural comparison of the different models shows that the cross-nested structure offers significant improvements over simple Nested Logit (NL) models, which in turn outperform the Multinomial Logit (MNL) model used as the base model

Allowing for intra-respondent variations in coefficients estimated on repeated choice data

Partly as a result of the increasing reliance on Stated Choice (SC) data, the vast majority of discrete choice modelling applications are now estimated on data containing multiple observations for each respondent. At the same time there has been growing interest in the representation of unexplained heterogeneity in choice data, using random coefficients models such as Mixed Multinomial Logit (MMNL). The presence of multiple observations for each respondent can indeed be a great asset in the identification of such variations in tastes. However, in this paper, we question the validity of the common assumption that tastes vary across respondents but stay constant across repeated choices for the same respondent. We extend the existing framework for the MMNL analysis of panel data by allowing for intra-respondent heterogeneity on top of inter-respondent heterogeneity. An empirical analysis making use of a SC dataset for route choice confirms our hypotheses and shows that superior performance is obtained by our more general model

Deal or no deal: can incentives encourage widespread adoption of intelligent speed adaptation devices?

Given the burden of injury, economic, environmental and social consequences associated with speeding, reducing road traffic speed remains a major priority. Intelligent speed adaptation (ISA) is a promising but controversial new in-vehicle system that provides drivers with support on the speed-control task. In order to model potential system uptake, this paper explores drivers’ preferences for two different types of ISA given a number of alternative fiscal incentives and non-fiscal measures, using a stated preference approach. As would be expected with such a contentious issue, the analysis revealed the presence of significant variations in sensitivities and preferences in the sample. While a non-negligible part of the sample population has such strong opposition to ISA that no reasonable discounts or incentives would lead to them buying or accepting such a system, there is also a large part of the population that, if given the right incentives, would be willing or even keen to equip their vehicle with an ISA device

Evaluation of advanced optimisation methods for estimating Mixed Logit models

The performances of different simulation-based estimation techniques for mixed logit modeling are evaluated. A quasi-Monte Carlo method (modified Latin hypercube sampling) is compared with a Monte Carlo algorithm with dynamic accuracy. The classic Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimization algorithm line-search approach and trust region methods, which have proved to be extremely powerful in nonlinear programming, are also compared. Numerical tests are performed on two real data sets: stated preference data for parking type collected in the United Kingdom, and revealed preference data for mode choice collected as part of a German travel diary survey. Several criteria are used to evaluate the approximation quality of the log likelihood function and the accuracy of the results and the associated estimation runtime. Results suggest that the trust region approach outperforms the BFGS approach and that Monte Carlo methods remain competitive with quasi-Monte Carlo methods in high-dimensional problems, especially when an adaptive optimization algorithm is used

Two-state shear diagrams for complex fluids in shear flow

The possible "phase diagrams'' for shear-induced phase transitions between two phases are collected. We consider shear-thickening and shear-thinning fluids, under conditions of both common strain rate and common stress in the two phases, and present the four fundamental shear stress vs. strain rate curves and discuss their concentration dependence. We outline how to construct more complicated phase diagrams, discuss in which class various experimental systems fall, and sketch how to reconstruct the phase diagrams from rheological measurements

Is the political business cycle for real?

This paper's macroeconomic model combines features from both real and political business cycle models. It augments a standard real business cycle tax model by allowing for varying levels of government partisanship and competence in order to replicate two important empirical regularities: First, that on average the economy expands early under Democratic presidents and contracts early under Republican presidents. Second, that presidents whose parties successfully retain the presidency have stronger-than-average growth in the second half of their terms. The model generates both of these features in conformity with U.S. post-World War II data.Business cycles

Is the Political Business Cycle for Real?

This paper constructs and examines a macroeconomic model which combines features from both real and political business cycle models. We augment a standard real business cycle tax model by allowing for varying levels of government partisanship and competence in order to replicate two important empirical regularities: First, that on average the economy expands early under Democratic Presidents and contracts early under Republican Presidents. Second, that Presidents whose parties successfully retain the presidency have stronger than average growth in the second half of their terms. The model generates both of these features that conform to U.S. Post World War II data.Political business cycle