Fuel dynamic simulations

Dynamic Simulation of Plate-Type Reformer and Combustor System for Molten Carbonate Fuel Cell... 

Dinh, B., Mauborgne, B., Baron, P. 1992. Dynamic simulation of extraction operations Application in nuclear fuel reprocessing. In European Symposium on Computer Aided Process Engineering-2, ESCAPE 2, October 5-7, Toulouse, France. 

Traverso A., Trasino F., Magistri F. (2006), Dynamic simulation of the anodic side of an integrated solid oxide fuel cell system. In 8th Biennial ASME Conference on Engineering Systems Design and Analysis, Turin, Italy, ESDA2006-95770. 

Sato, H., et al. (2007), Conceptual Design of the HTTR-IS Hydrogen Production System - Dynamic Simulation Code Development for the Advanced Process Heat Exchangers in the HTTR-IS system , Proc. of International Conference on Advanced Fuel Cycles and Systems (GLOBAL2007), Boise, ID, USA, pp. 812-819. 

Progress was also reported in modeling the reaction and transportation processes on fuel cell catalysts and through membranes, using multiple paradigms as well as starting from first principle quantum mechanics to train a reactive force field that can be applied for large scale molecular dynamics simulations. It is expected that the model would enable the conception, synthesis, fabrication, characterization, and development of advanced materials and structures for fuel cells . 

The next section gives a brief overview of the main computational techniques currently applied to catalytic problems. These techniques include ab initio electronic structure calculations, (ab initio) molecular dynamics, and Monte Carlo methods. The next three sections are devoted to particular applications of these techniques to catalytic and electrocatalytic issues. We focus on the interaction of CO and hydrogen with metal and alloy surfaces, both from quantum-chemical and statistical-mechanical points of view, as these processes play an important role in fuel-cell catalysis. We also demonstrate the role of the solvent in electrocatalytic bondbreaking reactions, using molecular dynamics simulations as well as extensive electronic structure and ab initio molecular dynamics calculations. Monte Carlo simulations illustrate the importance of lateral interactions, mixing, and surface diffusion in obtaining a correct kinetic description of catalytic processes. Finally, we summarize the main conclusions and give an outlook of the role of computational chemistry in catalysis and electrocatalysis. 

Membrane modelling has been considered from both the nano/microscopic and the macroscopic viewpoints, but little has been done to bridge these two limits. The breadth of microscopic modelling work for PEMs encompasses molecular dynamics simulations [17] and statistical mechanics modelling [18-21]. Most applications have focused on Nafion, and interestingly, some models even apply macroscopic transport relations to the microscopic transport within a pore of a membrane [41]. While the focus of this Chapter is on macroscopic models required for computational simulations of complete fuel cells [12,13,15], the proposed modelling framework is based on fundamental relations describing molecular transport phenomena. 

Moore RM,HauerK H,Friedman D, Cunningham J,Badrinarayanan P,Ramaswamy S and Eggert A (2005), A dynamic simulation tool for hydrogen fuel cell vehi-c es. Journal of Power Sources, 141,272-285. 

D dynamic simulations of various physical conditions such as coefficient of friction and extent of cells containing fuel assemblies. Resultant displacements and stresses are determined. 

For 2D and 3D dynamic simulations such on-line reduction are very computationally costly. A less CPU time intensive approach is to pre-define the combustion domains or zones in which a certain sub-set of the detailed mechanism is used. This is often used for diffusion flame calculations where the domains can be defined by the fuel rich and the fuel lean zones. Hence, schemes that find the smallest chemical sub-set locally in time or space have been proposed e.g. by Schwer et al. (Schwer et al., 2003)). Here each computational cell was assigned a certain sub-mechanism based on a set of physical criteria such as temperature, pressure, species concentrations etc. For highly turbulent flames where these criteria can change rapidly and steeply from cell to cell, this method can be demanding. A single criterion was therefore proposed by Lovas et al. (Lovas et al., 2010), where the sub-mechanism was chosen based on mixture fraction alone. This approach will act as example of implementation of adaptive... 

Floyd J. Multi-parameter, multiple fuel mixture fraction combustion model for fire dynamics simulator. US Department of Commerce Building and Fire Research Laboratory, National Institute of Standards and Technology 2008. 

Figure 5.59 Dynamic simulation of the start-up fuel processor (33 kWth) S/C = 0 O/C = 0.94 behaviour of an autothermal gasoline reformer 60 Lmin air addition to the water-gas shift coupled to a heat-exchanger for feed pre-heating reactor. Right gas composition downstream of and a water-gas shift reactor both reactors were the autothermal reformer (ATR) and the high pre-heated for 5 s with 2.5-kWei energy. Left temperature water-gas shift reactor (HTS)...

Chen et al. [452] developed start-up strategies for a 3-kWei methane fuel processor through dynamic simulations. The experimental fuel processor is shown in Figure 5.64. It was composed of two heat-exchangers for feed pre-heating, an autothermal reformer, three water-gas shift stages and three stages for preferential... 

In this chapter we will review the recent developments in simulating and modelling proton transport. We will put a special emphasis on studies employing classical and quantum molecular-dynamics simulations, but also include basic studies that have focussed on model systems using accurate quantum-chemical methods. Proton-transport and dilfusion phenomena in liquids - such as water, inorganic acids, or organic liquids - will be discussed as well as in biomolecules, solid-state materials, and at the solid-liquid interface. Many of these materials are used in proton-transporting fuel-cell membranes, so that membrane materials will be the focus of the last section. 

Peters R, Scharf F (2012) Computational fluid dynamic simulation using supercomputer calculation capacity. In Stolten D, Emonts B (eds) Fuel cell science and engineering—materials, processes, systems and technology. Wiley-VCH, Weinheim, pp 703-732... 

Xiao, Y., Yuan, J. Sundn, B. Process based large scale molecular dynamic simulation of a fuel cell catalyst layer. J. Electrochem. Soc. 159 (2012), B251-B258. 

Dynamic Simulation and Fuel Cell Control System... 

Dynamic Simulation Model for Fuel Cell Systems... 

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