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Path-based collective variables

D. Branduardi, M. De Vivo, N. Rega, V. Barone, and A. Cavalli,/. Chem. Theory Comput., 7(3), 539-543 (2011). Methyl Phosphate Dianion Hydrolysis in Solution Characterized by Path Collective Variables Coupled with DFT-Based Enhanced Sampling Simulations. [Pg.47]

The results presented in this chapter are based on a GT-Power model of a six cylinder heavy-duty diesel engine with a variable geometry turbocharger (VGT) and an exhaust gas recirculation (EGR) system. This model was calibrated using steady-state data collected experimentally and then validated using transient data. For the steady-state calibration, each of the actuator models were tuned to ensure that the VGT and EGR actuators affect the air path in a manner consistent with the experimental data. Quantities such as the fresh air flow, EGR flow, turbine speed, exhaust pressure and intake pressure were all analyzed. Because the specific fuel consumption and NOx production predictions are so important to the selection of the fueling parameters, particular attention was given to the predictive combustion model. The correlations between the experimental and predicted brake spjecific fuel consumption... [Pg.394]


See other pages where Path-based collective variables is mentioned: [Pg.23]    [Pg.57]    [Pg.109]    [Pg.30]    [Pg.173]    [Pg.157]    [Pg.113]    [Pg.13]    [Pg.243]    [Pg.1923]   
See also in sourсe #XX -- [ Pg.30 , Pg.31 ]




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Base variable

Collection Variables

Collective variable

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