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Aims.The goal is to develop a database of rate coefficients for rotational state-to-state transitions in H2O + H2O collisions that is suitable for the modeling of energy transfer in nonequilibrium conditions, in which the distribution of rotational states of H2O deviates from local thermodynamic equilibrium. Methods.A two-temperature model was employed that assumed that although there is no equilibrium between all possible degrees of freedom in the system, the translational and rotational degrees of freedom can be expected to achieve their own equilibria independently, and that they can be approximately characterized by Boltzmann distributions at two different temperatures,TkinandTrot. Results.Upon introducing our new parameterization of the collisional rates, taking into account their dependence on bothTkinandTrot, we find a change of up to 20% in the H2O rotational level populations for both ortho and para-H2O for the part of the cometary coma where the nonequilibrium regime occurs.
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The Effect of Population Flow on Epidemic Spread: Analysis and Control
In this paper, we present a discrete-time networked SEIR model using population flow, its derivation, and assumptions under which this model is well defined. We identify properties of the system’s equilibria, namely the healthy states. We show that the set of healthy states is asymptotically stable, and that the value of the equilibria becomes equal across all sub-populations as a result of the network flow model. Furthermore, we explore closed-loop feedback control of the system by limiting flow between sub-populations as a function of the current infected states. These results are illustrated via simulation based on flight traffic between major airports in the United States. We find that a flow restriction strategy combined with a vaccine roll-out significantly reduces the total number of infections over the course of an epidemic, given that the initial flow restriction response is not delayed.
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- PAR ID:
- 10320297
- Date Published:
- Journal Name:
- 2021 60th IEEE Conference on Decision and Control (CDC)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/CDC45484.2021.9683081
