A path-following driver-vehicle model with neuromuscular dynamics, including measured and simulated responses to a step in steering angle overlay

An existing driver-vehicle model with neuromuscular dynamics is improved in the areas of cognitive delay, intrinsic muscle dynamics and alpha-gamma co-activation. The model is used to investigate the influence of steering torque feedback and neuromuscular dynamics on the vehicle response to lateral force disturbances. When steering torque feedback is present, it is found that the longitudinal position of the lateral disturbance has a significant influence on whether the drivers reflex response reinforces or attenuates the effect of the disturbance. The response to angle and torque overlay inputs to the steering system is also investigated. The presence of the steering torque feedback reduced the disturbing effect of torque overlay and angle overlay inputs. Reflex action reduced the disturbing effect of a torque overlay input, but increased the disturbing effect of an angle overlay input. Experiments on a driving simulator showed that measured handwheel angle response to an angle overlay input was consistent with the response predicted by the model with reflex action. However, there was significant intra-and inter-subject variability. The results highlight the significance of a drivers neuromuscular dynamics in determining the vehicle response to disturbances. © 2012 Copyright Taylor and Francis Group, LLC.

Bayesian interpolation in a dynamic sinusoidal model with application to packet-loss concealment

In this paper, we consider Bayesian interpolation and parameter estimation in a dynamic sinusoidal model. This model is more flexible than the static sinusoidal model since it enables the amplitudes and phases of the sinusoids to be time-varying. For the dynamic sinusoidal model, we derive a Bayesian inference scheme for the missing observations, hidden states and model parameters of the dynamic model. The inference scheme is based on a Markov chain Monte Carlo method known as Gibbs sampler. We illustrate the performance of the inference scheme to the application of packet-loss concealment of lost audio and speech packets. © EURASIP, 2010.

Validation of a lattice Boltzmann model for gas-solid reactions with experiments

A lattice Boltzmann method is used to model gas-solid reactions where the composition of both the gas and solid phase changes with time, while the boundary between phases remains fixed. The flow of the bulk gas phase is treated using a multiple relaxation time MRT D3Q19 model; the dilute reactant is treated as a passive scalar using a single relaxation time BGK D3Q7 model with distinct inter- and intraparticle diffusivities. A first-order reaction is incorporated by modifying the method of Sullivan et al. [13] to include the conversion of a solid reactant. The detailed computational model is able to capture the multiscale physics encountered in reactor systems. Specifically, the model reproduced steady state analytical solutions for the reaction of a porous catalyst sphere (pore scale) and empirical solutions for mass transfer to the surface of a sphere at Re=10 (particle scale). Excellent quantitative agreement between the model and experiments for the transient reduction of a single, porous sphere of Fe 2O 3 to Fe 3O 4 in CO at 1023K and 10 5Pa is demonstrated. Model solutions for the reduction of a packed bed of Fe 2O 3 (reactor scale) at identical conditions approached those of experiments after 25 s, but required prohibitively long processor times. The presented lattice Boltzmann model resolved successfully mass transport at the pore, particle and reactor scales and highlights the relevance of LB methods for modelling convection, diffusion and reaction physics. © 2012 Elsevier Inc.