Battery Charging in Collision Models with Bayesian Risk Strategies

We constructed a collision model where measurements in the system, together with a Bayesian decision rule, are used to classify the incoming ancillas as having either high or low ergotropy (maximum extractable work). The former are allowed to leave, while the latter are redirected for further processing, aimed at increasing their ergotropy further. The ancillas play the role of a quantum battery, and the collision model, therefore, implements a Maxwell demon. To make the process autonomous and with a well-defined limit cycle, the information collected by the demon is reset after each collision by means of a cold heat bath.

Hard versus soft impact modeling of vibro-impact systems with a moving base

Soft and hard impact models applied to modeling of vibro-impact systems with a moving base are discussed. The conditions under which two collision models are equivalent in terms of equal energy dissipation are derived. These conditions differ from those presented in the literature. It is shown that in the case of a stiff, harmonically moving base with a low rate of energy dissipation, both methods yield the same results, but an application of the soft impact model to either the base with low stiffness or even the stiff base with a high rate of energy dissipation leads to different results from the ones for the hard impact model.

Calibration of highway safety manual predictive models and validation of safety performance funtions for canadian urban/suburban intersections

In this research, the HSM predictive models for collisions on urban/suburban arterials are calibrated for collision data from the City of Toronto. It has been found that the use of calibration factors for applying HSM models to Toronto intersection data is not appropriate. New collision models are therefore developed by using local data. The HSM and Toronto models are then calibrated to City of Edmonton intersection collision data to determine whether it is better to calibrate HSM models for a Canadian jurisdiction or models from another Canadian jurisdiction. A related aspect of the research is the investigation of models for crash types. There is no safety performance function (SPF) available in the HSM to predict rear end collisions. Instead, rear end collisions are estimated as a proportion of predicted multivehicle collisions. To overcome this deficiency, Toronto data are used in the estimation of models for rear end collisions.

Calibration of highway safety manual predictive models and validation of safety performance funtions for canadian urban/suburban intersections

In this research, the HSM predictive models for collisions on urban/suburban arterials are calibrated for collision data from the City of Toronto. It has been found that the use of calibration factors for applying HSM models to Toronto intersection data is not appropriate. New collision models are therefore developed by using local data. The HSM and Toronto models are then calibrated to City of Edmonton intersection collision data to determine whether it is better to calibrate HSM models for a Canadian jurisdiction or models from another Canadian jurisdiction. A related aspect of the research is the investigation of models for crash types. There is no safety performance function (SPF) available in the HSM to predict rear end collisions. Instead, rear end collisions are estimated as a proportion of predicted multivehicle collisions. To overcome this deficiency, Toronto data are used in the estimation of models for rear end collisions.