scholarly journals Stochastic time-dependent DFT with optimally tuned range-separated hybrids: Application to excitonic effects in large phosphorene sheets

2019 ◽  
Vol 150 (18) ◽  
pp. 184118 ◽  
Author(s):  
Vojtěch Vlček ◽  
Roi Baer ◽  
Daniel Neuhauser
Keyword(s):  
Time Dependent ◽  
Excitonic Effects ◽  
Stochastic Time

scholarly journals Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Shichao Sun ◽  
Zhengyu Duan ◽  
Dongyuan Yang
Keyword(s):  
Large Scale ◽  
Time Window ◽  
Transportation Networks ◽  
Optimal Path ◽  
Time Dependent ◽  
Travel Times ◽  
Urban Network ◽  
Routing Problem ◽  
On The Road ◽  
Stochastic Time

This paper addressed the vehicle routing problem (VRP) in large-scale urban transportation networks with stochastic time-dependent (STD) travel times. The subproblem which is how to find the optimal path connecting any pair of customer nodes in a STD network was solved through a robust approach without requiring the probability distributions of link travel times. Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP), and algorithms for such TD-VRPs can also be introduced to obtain the solution. Numerical experiments were conducted to address STD-VRPTW of practical sizes on a real world urban network, demonstrated here on the road network of Shenzhen, China. The stochastic time-dependent link travel times of the network were calibrated by historical floating car data. A route construction algorithm was applied to solve the STD problem in 4 delivery scenarios efficiently. The computational results showed that the proposed STD-VRPTW model can improve the level of customer service by satisfying the time-window constraint under any circumstances. The improvement can be very significant especially for large-scale network delivery tasks with no more increase in cost and environmental impacts.

Benchmarking the stochastic time-dependent variational approach for excitation dynamics in molecular aggregates

2016 ◽  
Vol 481 ◽  
pp. 108-116 ◽  
Author(s):  
Vladimir Chorošajev ◽  
Andrius Gelzinis ◽  
Leonas Valkunas ◽  
Darius Abramavicius
Keyword(s):  
Variational Approach ◽  
Time Dependent ◽  
Molecular Aggregates ◽  
Stochastic Time ◽  
Excitation Dynamics

scholarly journals Representing time-dependent freezing behaviour in immersion mode ice nucleation

2014 ◽  
Vol 14 (2) ◽  
pp. 1399-1442 ◽  
Author(s):  
R. J. Herbert ◽  
B. J. Murray ◽  
T. F. Whale ◽  
S. J. Dobbie ◽  
J. D. Atkinson
Keyword(s):  
Experimental Studies ◽  
Ice Nucleation ◽  
Time Dependent ◽  
Computationally Efficient ◽  
Routine Testing ◽  
Experimental Systems ◽  
Quantitative Understanding ◽  
Efficient Representation ◽  
The Impact ◽  
Stochastic Time

Abstract. In order to understand the impact of ice formation in clouds, a quantitative understanding of ice nucleation is required, along with an accurate and efficient representation for use in cloud resolving models. Ice nucleation by atmospherically relevant particle types is complicated by inter-particle variability in nucleating ability, as well as a stochastic, time-dependent, nature inherent to nucleation. Here we present a new and computationally efficient Framework for Reconciling Observable Stochastic Time-dependence (FROST) in immersion mode ice nucleation. This framework is underpinned by the finding that the temperature dependence of the nucleation rate coefficient controls the residence-time and cooling-rate dependence of freezing. It is shown that this framework can be used to reconcile experimental data obtained on different time scales with different experimental systems, and it also provides a simple way of representing the complexities of ice nucleation in cloud resolving models. The routine testing and reporting of time-dependent behaviour in future experimental studies is recommended, along with the practice of presenting normalised datasets following the methods outlined here.

A latent-class adaptive routing choice model in stochastic time-dependent networks

2019 ◽  
Vol 124 ◽  
pp. 1-17 ◽  
Author(s):  
Jing Ding-Mastera ◽  
Song Gao ◽  
Erik Jenelius ◽  
Mahmood Rahmani ◽  
Moshe Ben-Akiva
Keyword(s):  
Latent Class ◽  
Choice Model ◽  
Adaptive Routing ◽  
Time Dependent ◽  
Stochastic Time
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