Model Simulation on Parallel Computers

1997 ◽  
pp. 71-92
Author(s):  
Giorgio Pauletto
Keyword(s):  
Model Simulation ◽  
Parallel Computers

Model, simulation and experiments for a Buoyancy Organic Rankine Cycle

2020 ◽  
Vol 92 (1) ◽  
pp. 10906
Author(s):  
Jeroen Schoenmaker ◽  
Pâmella Gonçalves Martins ◽  
Guilherme Corsi Miranda da Silva ◽  
Julio Carlos Teixeira
Keyword(s):  
Model Simulation ◽  
Organic Rankine Cycle ◽  
Thermodynamic Cycle ◽  
Rankine Cycle ◽  
Test Body ◽  
Working Fluid ◽  
Proof Of Concept ◽  
Energy Scenario ◽  
New Type ◽  
Fluid Reservoir

Organic Rankine Cycle (ORC) systems are increasingly gaining relevance in the renewable and sustainable energy scenario. Recently our research group published a manuscript identifying a new type of thermodynamic cycle entitled Buoyancy Organic Rankine Cycle (BORC) [J. Schoenmaker, J.F.Q. Rey, K.R. Pirota, Renew. Energy 36, 999 (2011)]. In this work we present two main contributions. First, we propose a refined thermodynamic model for BORC systems accounting for the specific heat of the working fluid. Considering the refined model, the efficiencies for Pentane and Dichloromethane at temperatures up to 100 °C were estimated to be 17.2%. Second, we show a proof of concept BORC system using a 3 m tall, 0.062 m diameter polycarbonate tube as a column-fluid reservoir. We used water as a column fluid. The thermal stability and uniformity throughout the tube has been carefully simulated and verified experimentally. After the thermal parameters of the water column have been fully characterized, we developed a test body to allow an adequate assessment of the BORC-system's efficiency. We obtained 0.84% efficiency for 43.8 °C working temperature. This corresponds to 35% of the Carnot efficiency calculated for the same temperature difference. Limitations of the model and the apparatus are put into perspective, pointing directions for further developments of BORC systems.

Quantitative Ranking of Ligand Binding Kinetics with a Multiscale Milestoning Simulation Approach

2018 ◽  
Author(s):  
Benjamin R. Jagger ◽  
Christoper T. Lee ◽  
Rommie Amaro
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Small Molecule ◽  
Brownian Dynamics ◽  
Model Simulation ◽  
Computational Cost ◽  
Lead Selection ◽  
Delta G ◽  
Dynamics Simulations

<p>The ranking of small molecule binders by their kinetic (kon and koff) and thermodynamic (delta G) properties can be a valuable metric for lead selection and optimization in a drug discovery campaign, as these quantities are often indicators of in vivo efficacy. Efficient and accurate predictions of these quantities can aid the in drug discovery effort, acting as a screening step. We have previously described a hybrid molecular dynamics, Brownian dynamics, and milestoning model, Simulation Enabled Estimation of Kinetic Rates (SEEKR), that can predict kon’s, koff’s, and G’s. Here we demonstrate the effectiveness of this approach for ranking a series of seven small molecule compounds for the model system, -cyclodextrin, based on predicted kon’s and koff’s. We compare our results using SEEKR to experimentally determined rates as well as rates calculated using long-timescale molecular dynamics simulations and show that SEEKR can effectively rank the compounds by koff and G with reduced computational cost. We also provide a discussion of convergence properties and sensitivities of calculations with SEEKR to establish “best practices” for its future use.</p>

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